notebooks/Advanced_Regression_Turbofan.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Advanced Regression\n",
    "\n",
    "Regression models continuous-valued functions, i.e. it is used to predict missing or unavailable numerical data values rather than class labels. The inputs for regression can be real values or discrete input variables. When there are multiple input variables, it is known as a multivariate regression problem. When the input variables are ordered by time, it is known as a time series forecasting problem.\n",
    "\n",
    "In this notebook, we use a data set from NASA: Turbofan Engine Degradation Simulation 9https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/). This is a multiple multivariate time series data set consisting of sensor readings from a fleet of simulated aircraft gas turbine engines. Our goal is to predict the remaining useful life of the engine units.\n",
    "\n",
    "We will first do some exploratory data analysis, then prepare our data for modelling, then finally run some regression models for comparison. We will use three different algorithms: a neural network, a kernel ridge regression, and a random forest regression.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load dependencies\n",
    "\n",
    "First, we will load the dependencies for this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn import metrics\n",
    "from scipy.stats import pearsonr\n",
    "import tensorflow as tf\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "pd.set_option('max_columns', 30)\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.kernel_ridge import KernelRidge\n",
    "from sklearn.metrics import r2_score\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data\n",
    "\n",
    "We will now load the data required for this notebook. As mentioned, the data comes from the NASA Turbofan data sets. We have three different data sets: a training set, a testing set, and unsesson values for remaining useful life (RUL)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import types\n",
    "import pandas as pd\n",
    "from botocore.client import Config\n",
    "import ibm_boto3\n",
    "\n",
    "def __iter__(self): return 0\n",
    "\n",
    "# @hidden_cell\n",
    "# The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials.\n",
    "# You might want to remove those credentials before you share your notebook.\n",
    "client_9a1c599639334c4db6a099ac66965340 = ibm_boto3.client(service_name='s3',\n",
    "    ibm_api_key_id='<redacted>',\n",
    "    ibm_auth_endpoint=\"<redacted>\",\n",
    "    config=Config(signature_version='oauth'),\n",
    "    endpoint_url='<redacted>')\n",
    "\n",
    "# Your data file was loaded into a botocore.response.StreamingBody object.\n",
    "# Please read the documentation of ibm_boto3 and pandas to learn more about your possibilities to load the data.\n",
    "# ibm_boto3 documentation: https://ibm.github.io/ibm-cos-sdk-python/\n",
    "# pandas documentation: http://pandas.pydata.org/\n",
    "streaming_body_4 = client_9a1c599639334c4db6a099ac66965340.get_object(Bucket='<redacted>', Key='train_FD001.txt')['Body']\n",
    "# add missing __iter__ method, so pandas accepts body as file-like object\n",
    "if not hasattr(streaming_body_4, \"__iter__\"): streaming_body_4.__iter__ = types.MethodType( __iter__, streaming_body_4 ) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Your data file was loaded into a botocore.response.StreamingBody object.\n",
    "# Please read the documentation of ibm_boto3 and pandas to learn more about your possibilities to load the data.\n",
    "# ibm_boto3 documentation: https://ibm.github.io/ibm-cos-sdk-python/\n",
    "# pandas documentation: http://pandas.pydata.org/\n",
    "streaming_body_5 = client_9a1c599639334c4db6a099ac66965340.get_object(Bucket='<redacted>', Key='test_FD001.txt')['Body']\n",
    "# add missing __iter__ method so pandas accepts body as file-like object\n",
    "if not hasattr(streaming_body_5, \"__iter__\"): streaming_body_5.__iter__ = types.MethodType( __iter__, streaming_body_5 )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Your data file was loaded into a botocore.response.StreamingBody object.\n",
    "# Please read the documentation of ibm_boto3 and pandas to learn more about your possibilities to load the data.\n",
    "# ibm_boto3 documentation: https://ibm.github.io/ibm-cos-sdk-python/\n",
    "# pandas documentation: http://pandas.pydata.org/\n",
    "streaming_body_6 = client_9a1c599639334c4db6a099ac66965340.get_object(Bucket='<redacted>', Key='RUL_FD001.txt')['Body']\n",
    "# add missing __iter__ method so pandas accepts body as file-like object\n",
    "if not hasattr(streaming_body_6, \"__iter__\"): streaming_body_6.__iter__ = types.MethodType( __iter__, streaming_body_6 ) \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis\n",
    "\n",
    "Before we get started with modelling, we need to get the data ready. Typically the first step is to take a closer look at the data set's features and associated values. Often, data is noisy, comes in large volumes, and may come from many different sources. Therefore, you need to understand your data before you can start preprocessing it. Some of the questions you will want to answer are:\n",
    "\n",
    "* What are the types of features in the data set?\n",
    "* What kind of values does each feature have?\n",
    "* Which features are discrete, and which are continuous-valued?\n",
    "* How are the values distributed in each feature?\n",
    "* Can we better understand the data through visualization?\n",
    "* Are there any outliers?\n",
    "* How similar are some data points to others?\n",
    "\n",
    "First, let's get the dimensions of the training data set. We can see that the data set has 20631 rows and 28 features or attributes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "exp_data = pd.read_csv(streaming_body_4, sep = ' ', header = None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20631, 28)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last two columns have NaN data, so we can remove those. We can also see that the first column is the unit and the second is the cycle. Let's rename the columns accordingly. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unit</th>\n",
       "      <th>cycle</th>\n",
       "      <th>op_setting1</th>\n",
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       "      <th>s1</th>\n",
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       "      <td>2388.06</td>\n",
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       "      <td>100.0</td>\n",
       "      <td>39.06</td>\n",
       "      <td>23.4190</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.15</td>\n",
       "      <td>1591.82</td>\n",
       "      <td>1403.14</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>553.75</td>\n",
       "      <td>2388.04</td>\n",
       "      <td>9044.07</td>\n",
       "      <td>1.3</td>\n",
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       "      <td>522.28</td>\n",
       "      <td>2388.07</td>\n",
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       "      <td>8.4318</td>\n",
       "      <td>0.03</td>\n",
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       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>23.4236</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.0043</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.35</td>\n",
       "      <td>1587.99</td>\n",
       "      <td>1404.20</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>554.26</td>\n",
       "      <td>2388.08</td>\n",
       "      <td>9052.94</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.27</td>\n",
       "      <td>522.42</td>\n",
       "      <td>2388.03</td>\n",
       "      <td>8133.23</td>\n",
       "      <td>8.4178</td>\n",
       "      <td>0.03</td>\n",
       "      <td>390</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.95</td>\n",
       "      <td>23.3442</td>\n",
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       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.35</td>\n",
       "      <td>1582.79</td>\n",
       "      <td>1401.87</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>554.45</td>\n",
       "      <td>2388.11</td>\n",
       "      <td>9049.48</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.13</td>\n",
       "      <td>522.86</td>\n",
       "      <td>2388.08</td>\n",
       "      <td>8133.83</td>\n",
       "      <td>8.3682</td>\n",
       "      <td>0.03</td>\n",
       "      <td>392</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.88</td>\n",
       "      <td>23.3739</td>\n",
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       "      <th>4</th>\n",
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       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
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       "      <td>2388.06</td>\n",
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       "      <td>100.0</td>\n",
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      ],
      "text/plain": [
       "   unit  cycle  op_setting1  op_setting2  op_setting3      s1      s2  \\\n",
       "0     1      1      -0.0007      -0.0004        100.0  518.67  641.82   \n",
       "1     1      2       0.0019      -0.0003        100.0  518.67  642.15   \n",
       "2     1      3      -0.0043       0.0003        100.0  518.67  642.35   \n",
       "3     1      4       0.0007       0.0000        100.0  518.67  642.35   \n",
       "4     1      5      -0.0019      -0.0002        100.0  518.67  642.37   \n",
       "\n",
       "        s3       s4     s5     s6      s7       s8       s9  s10    s11  \\\n",
       "0  1589.70  1400.60  14.62  21.61  554.36  2388.06  9046.19  1.3  47.47   \n",
       "1  1591.82  1403.14  14.62  21.61  553.75  2388.04  9044.07  1.3  47.49   \n",
       "2  1587.99  1404.20  14.62  21.61  554.26  2388.08  9052.94  1.3  47.27   \n",
       "3  1582.79  1401.87  14.62  21.61  554.45  2388.11  9049.48  1.3  47.13   \n",
       "4  1582.85  1406.22  14.62  21.61  554.00  2388.06  9055.15  1.3  47.28   \n",
       "\n",
       "      s12      s13      s14     s15   s16  s17   s18    s19    s20      s21  \n",
       "0  521.66  2388.02  8138.62  8.4195  0.03  392  2388  100.0  39.06  23.4190  \n",
       "1  522.28  2388.07  8131.49  8.4318  0.03  392  2388  100.0  39.00  23.4236  \n",
       "2  522.42  2388.03  8133.23  8.4178  0.03  390  2388  100.0  38.95  23.3442  \n",
       "3  522.86  2388.08  8133.83  8.3682  0.03  392  2388  100.0  38.88  23.3739  \n",
       "4  522.19  2388.04  8133.80  8.4294  0.03  393  2388  100.0  38.90  23.4044  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_data = exp_data[list(range(0, 26))]\n",
    "exp_data.rename(columns = {0 : 'unit', 1 : 'cycle', 2 : 'op_setting1', 3 : 'op_setting2', 4 : 'op_setting3', 5 : 's1', 6 : 's2', 7 : 's3', 8 :'s4', 9 : 's5', 10 : 's6', 11 : 's7', 12 : 's8', 13 : 's9', 14 : 's10', 15 : 's11', 16 : 's12', 17 : 's13', 18 : 's14', 19 : 's15', 20 : 's16', 21 : 's17', 22 : 's18', 23 : 's19', 24 : 's20', 25 : 's21'}, inplace = True)\n",
    "exp_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see some aggregated statistics for the data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>unit</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>51.506568</td>\n",
       "      <td>2.922763e+01</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>77.0000</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cycle</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>108.807862</td>\n",
       "      <td>6.888099e+01</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>104.0000</td>\n",
       "      <td>156.0000</td>\n",
       "      <td>362.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>op_setting1</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>2.187313e-03</td>\n",
       "      <td>-0.0087</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>op_setting2</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2.930621e-04</td>\n",
       "      <td>-0.0006</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>op_setting3</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s1</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>518.670000</td>\n",
       "      <td>6.537152e-11</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s2</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>642.680934</td>\n",
       "      <td>5.000533e-01</td>\n",
       "      <td>641.2100</td>\n",
       "      <td>642.3250</td>\n",
       "      <td>642.6400</td>\n",
       "      <td>643.0000</td>\n",
       "      <td>644.5300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s3</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>1590.523119</td>\n",
       "      <td>6.131150e+00</td>\n",
       "      <td>1571.0400</td>\n",
       "      <td>1586.2600</td>\n",
       "      <td>1590.1000</td>\n",
       "      <td>1594.3800</td>\n",
       "      <td>1616.9100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s4</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>1408.933782</td>\n",
       "      <td>9.000605e+00</td>\n",
       "      <td>1382.2500</td>\n",
       "      <td>1402.3600</td>\n",
       "      <td>1408.0400</td>\n",
       "      <td>1414.5550</td>\n",
       "      <td>1441.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s5</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>14.620000</td>\n",
       "      <td>3.394700e-12</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s6</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>21.609803</td>\n",
       "      <td>1.388985e-03</td>\n",
       "      <td>21.6000</td>\n",
       "      <td>21.6100</td>\n",
       "      <td>21.6100</td>\n",
       "      <td>21.6100</td>\n",
       "      <td>21.6100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s7</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>553.367711</td>\n",
       "      <td>8.850923e-01</td>\n",
       "      <td>549.8500</td>\n",
       "      <td>552.8100</td>\n",
       "      <td>553.4400</td>\n",
       "      <td>554.0100</td>\n",
       "      <td>556.0600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s8</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>2388.096652</td>\n",
       "      <td>7.098548e-02</td>\n",
       "      <td>2387.9000</td>\n",
       "      <td>2388.0500</td>\n",
       "      <td>2388.0900</td>\n",
       "      <td>2388.1400</td>\n",
       "      <td>2388.5600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s9</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>9065.242941</td>\n",
       "      <td>2.208288e+01</td>\n",
       "      <td>9021.7300</td>\n",
       "      <td>9053.1000</td>\n",
       "      <td>9060.6600</td>\n",
       "      <td>9069.4200</td>\n",
       "      <td>9244.5900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s10</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>1.300000</td>\n",
       "      <td>4.660829e-13</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s11</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>47.541168</td>\n",
       "      <td>2.670874e-01</td>\n",
       "      <td>46.8500</td>\n",
       "      <td>47.3500</td>\n",
       "      <td>47.5100</td>\n",
       "      <td>47.7000</td>\n",
       "      <td>48.5300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s12</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>521.413470</td>\n",
       "      <td>7.375534e-01</td>\n",
       "      <td>518.6900</td>\n",
       "      <td>520.9600</td>\n",
       "      <td>521.4800</td>\n",
       "      <td>521.9500</td>\n",
       "      <td>523.3800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s13</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>2388.096152</td>\n",
       "      <td>7.191892e-02</td>\n",
       "      <td>2387.8800</td>\n",
       "      <td>2388.0400</td>\n",
       "      <td>2388.0900</td>\n",
       "      <td>2388.1400</td>\n",
       "      <td>2388.5600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s14</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>8143.752722</td>\n",
       "      <td>1.907618e+01</td>\n",
       "      <td>8099.9400</td>\n",
       "      <td>8133.2450</td>\n",
       "      <td>8140.5400</td>\n",
       "      <td>8148.3100</td>\n",
       "      <td>8293.7200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s15</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>8.442146</td>\n",
       "      <td>3.750504e-02</td>\n",
       "      <td>8.3249</td>\n",
       "      <td>8.4149</td>\n",
       "      <td>8.4389</td>\n",
       "      <td>8.4656</td>\n",
       "      <td>8.5848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s16</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>1.556432e-14</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s17</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>393.210654</td>\n",
       "      <td>1.548763e+00</td>\n",
       "      <td>388.0000</td>\n",
       "      <td>392.0000</td>\n",
       "      <td>393.0000</td>\n",
       "      <td>394.0000</td>\n",
       "      <td>400.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s18</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>2388.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s19</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s20</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>38.816271</td>\n",
       "      <td>1.807464e-01</td>\n",
       "      <td>38.1400</td>\n",
       "      <td>38.7000</td>\n",
       "      <td>38.8300</td>\n",
       "      <td>38.9500</td>\n",
       "      <td>39.4300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s21</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>23.289705</td>\n",
       "      <td>1.082509e-01</td>\n",
       "      <td>22.8942</td>\n",
       "      <td>23.2218</td>\n",
       "      <td>23.2979</td>\n",
       "      <td>23.3668</td>\n",
       "      <td>23.6184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               count         mean           std        min        25%  \\\n",
       "unit         20631.0    51.506568  2.922763e+01     1.0000    26.0000   \n",
       "cycle        20631.0   108.807862  6.888099e+01     1.0000    52.0000   \n",
       "op_setting1  20631.0    -0.000009  2.187313e-03    -0.0087    -0.0015   \n",
       "op_setting2  20631.0     0.000002  2.930621e-04    -0.0006    -0.0002   \n",
       "op_setting3  20631.0   100.000000  0.000000e+00   100.0000   100.0000   \n",
       "s1           20631.0   518.670000  6.537152e-11   518.6700   518.6700   \n",
       "s2           20631.0   642.680934  5.000533e-01   641.2100   642.3250   \n",
       "s3           20631.0  1590.523119  6.131150e+00  1571.0400  1586.2600   \n",
       "s4           20631.0  1408.933782  9.000605e+00  1382.2500  1402.3600   \n",
       "s5           20631.0    14.620000  3.394700e-12    14.6200    14.6200   \n",
       "s6           20631.0    21.609803  1.388985e-03    21.6000    21.6100   \n",
       "s7           20631.0   553.367711  8.850923e-01   549.8500   552.8100   \n",
       "s8           20631.0  2388.096652  7.098548e-02  2387.9000  2388.0500   \n",
       "s9           20631.0  9065.242941  2.208288e+01  9021.7300  9053.1000   \n",
       "s10          20631.0     1.300000  4.660829e-13     1.3000     1.3000   \n",
       "s11          20631.0    47.541168  2.670874e-01    46.8500    47.3500   \n",
       "s12          20631.0   521.413470  7.375534e-01   518.6900   520.9600   \n",
       "s13          20631.0  2388.096152  7.191892e-02  2387.8800  2388.0400   \n",
       "s14          20631.0  8143.752722  1.907618e+01  8099.9400  8133.2450   \n",
       "s15          20631.0     8.442146  3.750504e-02     8.3249     8.4149   \n",
       "s16          20631.0     0.030000  1.556432e-14     0.0300     0.0300   \n",
       "s17          20631.0   393.210654  1.548763e+00   388.0000   392.0000   \n",
       "s18          20631.0  2388.000000  0.000000e+00  2388.0000  2388.0000   \n",
       "s19          20631.0   100.000000  0.000000e+00   100.0000   100.0000   \n",
       "s20          20631.0    38.816271  1.807464e-01    38.1400    38.7000   \n",
       "s21          20631.0    23.289705  1.082509e-01    22.8942    23.2218   \n",
       "\n",
       "                   50%        75%        max  \n",
       "unit           52.0000    77.0000   100.0000  \n",
       "cycle         104.0000   156.0000   362.0000  \n",
       "op_setting1     0.0000     0.0015     0.0087  \n",
       "op_setting2     0.0000     0.0003     0.0006  \n",
       "op_setting3   100.0000   100.0000   100.0000  \n",
       "s1            518.6700   518.6700   518.6700  \n",
       "s2            642.6400   643.0000   644.5300  \n",
       "s3           1590.1000  1594.3800  1616.9100  \n",
       "s4           1408.0400  1414.5550  1441.4900  \n",
       "s5             14.6200    14.6200    14.6200  \n",
       "s6             21.6100    21.6100    21.6100  \n",
       "s7            553.4400   554.0100   556.0600  \n",
       "s8           2388.0900  2388.1400  2388.5600  \n",
       "s9           9060.6600  9069.4200  9244.5900  \n",
       "s10             1.3000     1.3000     1.3000  \n",
       "s11            47.5100    47.7000    48.5300  \n",
       "s12           521.4800   521.9500   523.3800  \n",
       "s13          2388.0900  2388.1400  2388.5600  \n",
       "s14          8140.5400  8148.3100  8293.7200  \n",
       "s15             8.4389     8.4656     8.5848  \n",
       "s16             0.0300     0.0300     0.0300  \n",
       "s17           393.0000   394.0000   400.0000  \n",
       "s18          2388.0000  2388.0000  2388.0000  \n",
       "s19           100.0000   100.0000   100.0000  \n",
       "s20            38.8300    38.9500    39.4300  \n",
       "s21            23.2979    23.3668    23.6184  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_data.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's assign the number max number cycles for each unit and the remaining useful per time stamp."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_cycles = exp_data.groupby(['unit']).agg({'cycle' : 'max'}).reset_index()\n",
    "total_cycles.rename(columns = {'cycle' : 'total_cycles'}, inplace = True)\n",
    "    \n",
    "exp_data = exp_data.merge(total_cycles, how = 'left', left_on = 'unit', right_on = 'unit')\n",
    "exp_data['RUL'] = exp_data.apply(lambda r: int(r['total_cycles'] - r['cycle']), axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unit</th>\n",
       "      <th>cycle</th>\n",
       "      <th>op_setting1</th>\n",
       "      <th>op_setting2</th>\n",
       "      <th>op_setting3</th>\n",
       "      <th>s1</th>\n",
       "      <th>s2</th>\n",
       "      <th>s3</th>\n",
       "      <th>s4</th>\n",
       "      <th>s5</th>\n",
       "      <th>s6</th>\n",
       "      <th>s7</th>\n",
       "      <th>s8</th>\n",
       "      <th>s9</th>\n",
       "      <th>s10</th>\n",
       "      <th>s11</th>\n",
       "      <th>s12</th>\n",
       "      <th>s13</th>\n",
       "      <th>s14</th>\n",
       "      <th>s15</th>\n",
       "      <th>s16</th>\n",
       "      <th>s17</th>\n",
       "      <th>s18</th>\n",
       "      <th>s19</th>\n",
       "      <th>s20</th>\n",
       "      <th>s21</th>\n",
       "      <th>total_cycles</th>\n",
       "      <th>RUL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.0007</td>\n",
       "      <td>-0.0004</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>641.82</td>\n",
       "      <td>1589.70</td>\n",
       "      <td>1400.60</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>554.36</td>\n",
       "      <td>2388.06</td>\n",
       "      <td>9046.19</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.47</td>\n",
       "      <td>521.66</td>\n",
       "      <td>2388.02</td>\n",
       "      <td>8138.62</td>\n",
       "      <td>8.4195</td>\n",
       "      <td>0.03</td>\n",
       "      <td>392</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>39.06</td>\n",
       "      <td>23.4190</td>\n",
       "      <td>192</td>\n",
       "      <td>191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.15</td>\n",
       "      <td>1591.82</td>\n",
       "      <td>1403.14</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>553.75</td>\n",
       "      <td>2388.04</td>\n",
       "      <td>9044.07</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.49</td>\n",
       "      <td>522.28</td>\n",
       "      <td>2388.07</td>\n",
       "      <td>8131.49</td>\n",
       "      <td>8.4318</td>\n",
       "      <td>0.03</td>\n",
       "      <td>392</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>23.4236</td>\n",
       "      <td>192</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.0043</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.35</td>\n",
       "      <td>1587.99</td>\n",
       "      <td>1404.20</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>554.26</td>\n",
       "      <td>2388.08</td>\n",
       "      <td>9052.94</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.27</td>\n",
       "      <td>522.42</td>\n",
       "      <td>2388.03</td>\n",
       "      <td>8133.23</td>\n",
       "      <td>8.4178</td>\n",
       "      <td>0.03</td>\n",
       "      <td>390</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.95</td>\n",
       "      <td>23.3442</td>\n",
       "      <td>192</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0007</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.35</td>\n",
       "      <td>1582.79</td>\n",
       "      <td>1401.87</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>554.45</td>\n",
       "      <td>2388.11</td>\n",
       "      <td>9049.48</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.13</td>\n",
       "      <td>522.86</td>\n",
       "      <td>2388.08</td>\n",
       "      <td>8133.83</td>\n",
       "      <td>8.3682</td>\n",
       "      <td>0.03</td>\n",
       "      <td>392</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.88</td>\n",
       "      <td>23.3739</td>\n",
       "      <td>192</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>-0.0019</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>100.0</td>\n",
       "      <td>518.67</td>\n",
       "      <td>642.37</td>\n",
       "      <td>1582.85</td>\n",
       "      <td>1406.22</td>\n",
       "      <td>14.62</td>\n",
       "      <td>21.61</td>\n",
       "      <td>554.00</td>\n",
       "      <td>2388.06</td>\n",
       "      <td>9055.15</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47.28</td>\n",
       "      <td>522.19</td>\n",
       "      <td>2388.04</td>\n",
       "      <td>8133.80</td>\n",
       "      <td>8.4294</td>\n",
       "      <td>0.03</td>\n",
       "      <td>393</td>\n",
       "      <td>2388</td>\n",
       "      <td>100.0</td>\n",
       "      <td>38.90</td>\n",
       "      <td>23.4044</td>\n",
       "      <td>192</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   unit  cycle  op_setting1  op_setting2  op_setting3      s1      s2  \\\n",
       "0     1      1      -0.0007      -0.0004        100.0  518.67  641.82   \n",
       "1     1      2       0.0019      -0.0003        100.0  518.67  642.15   \n",
       "2     1      3      -0.0043       0.0003        100.0  518.67  642.35   \n",
       "3     1      4       0.0007       0.0000        100.0  518.67  642.35   \n",
       "4     1      5      -0.0019      -0.0002        100.0  518.67  642.37   \n",
       "\n",
       "        s3       s4     s5     s6      s7       s8       s9  s10    s11  \\\n",
       "0  1589.70  1400.60  14.62  21.61  554.36  2388.06  9046.19  1.3  47.47   \n",
       "1  1591.82  1403.14  14.62  21.61  553.75  2388.04  9044.07  1.3  47.49   \n",
       "2  1587.99  1404.20  14.62  21.61  554.26  2388.08  9052.94  1.3  47.27   \n",
       "3  1582.79  1401.87  14.62  21.61  554.45  2388.11  9049.48  1.3  47.13   \n",
       "4  1582.85  1406.22  14.62  21.61  554.00  2388.06  9055.15  1.3  47.28   \n",
       "\n",
       "      s12      s13      s14     s15   s16  s17   s18    s19    s20      s21  \\\n",
       "0  521.66  2388.02  8138.62  8.4195  0.03  392  2388  100.0  39.06  23.4190   \n",
       "1  522.28  2388.07  8131.49  8.4318  0.03  392  2388  100.0  39.00  23.4236   \n",
       "2  522.42  2388.03  8133.23  8.4178  0.03  390  2388  100.0  38.95  23.3442   \n",
       "3  522.86  2388.08  8133.83  8.3682  0.03  392  2388  100.0  38.88  23.3739   \n",
       "4  522.19  2388.04  8133.80  8.4294  0.03  393  2388  100.0  38.90  23.4044   \n",
       "\n",
       "   total_cycles  RUL  \n",
       "0           192  191  \n",
       "1           192  190  \n",
       "2           192  189  \n",
       "3           192  188  \n",
       "4           192  187  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's examine the maximum number of cycles for each unit in the data set. It looks like most units last over 100 cycles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40f239f2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (16,12))\n",
    "fig.add_subplot(1,2,1)\n",
    "bar_labels = list(exp_data['unit'])\n",
    "bars = plt.bar(list(exp_data['unit']), exp_data['cycle'], color='green')\n",
    "plt.ylim([0, 400])\n",
    "plt.xlabel('Units', fontsize=16)\n",
    "plt.ylabel('Max. Cycles', fontsize=16)\n",
    "plt.title('Max. Cycles per unit in training set', fontsize=16)\n",
    "plt.xticks(np.arange(min(bar_labels)-1, max(bar_labels)-1, 5.0), fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization of operating conditions and sensors\n",
    "\n",
    "The following visualizes the operating conditions and some of different sensors of a particular unit. It shows that the sensors often different range of values and show differing patterns and trends over time i.e. some increasing, some flat, and some decreasing. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40f239fa58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "values = exp_data[exp_data.unit==1].values\n",
    "groups = [2,3, 4, 5, 6, 7, 8, 9, 10, 11,12,13]\n",
    "i = 1\n",
    "plt.figure(figsize=(10,20))\n",
    "for group in groups:\n",
    "\tplt.subplot(len(groups), 1, i)\n",
    "\tplt.plot(values[:, group])\n",
    "\tplt.title(exp_data.columns[group], y=0.5, loc='right')\n",
    "\ti += 1\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's display what a single sensor looks for multiple engine units. We can see that it increases over time towards a max of 2388.20 and the data looks quite noisy. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40e3de37f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8, 8))\n",
    "plt.plot(exp_data[exp_data.unit==1].cycle, exp_data[exp_data.unit==1].s8)\n",
    "plt.plot(exp_data[exp_data.unit==3].cycle, exp_data[exp_data.unit==3].s8)\n",
    "plt.plot(exp_data[exp_data.unit==4].cycle, exp_data[exp_data.unit==4].s8)\n",
    "plt.plot(exp_data[exp_data.unit==5].cycle, exp_data[exp_data.unit==5].s8)\n",
    "plt.plot(exp_data[exp_data.unit==6].cycle, exp_data[exp_data.unit==6].s8)\n",
    "plt.plot(exp_data[exp_data.unit==7].cycle, exp_data[exp_data.unit==7].s8)\n",
    "plt.plot(exp_data[exp_data.unit==8].cycle, exp_data[exp_data.unit==8].s8)\n",
    "plt.plot(exp_data[exp_data.unit==9].cycle, exp_data[exp_data.unit==9].s8)\n",
    "plt.plot(exp_data[exp_data.unit==10].cycle, exp_data[exp_data.unit==10].s8)\n",
    "plt.xlabel('# Cycles')\n",
    "plt.ylabel('Sensor measurements')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You might expect that sensors exhibit similar min and max values, even for different units. Let's see if we can confirm that with some data visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "minb = exp_data.groupby('unit', as_index=False).min().head(10)\n",
    "maxb = exp_data.groupby('unit', as_index=False).max().head(10)\n",
    "mmtable = minb.append(maxb, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40e437e7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,12))\n",
    "col = np.concatenate((np.repeat('orange', 10), np.repeat('green', 10)), axis=0)\n",
    "bar_labels = list(mmtable['unit'])\n",
    "x_pos = list(range(len(bar_labels)))\n",
    "bars = plt.bar(x_pos, mmtable['s8'], color=col)\n",
    "plt.ylim([2387.90, 2388.36])\n",
    "plt.xlabel('Units', fontsize=14)\n",
    "plt.ylabel('Measure s8', fontsize=14)\n",
    "plt.xticks(x_pos, bar_labels, fontsize=14)\n",
    "plt.yticks(fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at how our data set is looking now with these new features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>unit</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>51.506568</td>\n",
       "      <td>2.922763e+01</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>26.0000</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>77.0000</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cycle</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>108.807862</td>\n",
       "      <td>6.888099e+01</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>104.0000</td>\n",
       "      <td>156.0000</td>\n",
       "      <td>362.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>op_setting1</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>2.187313e-03</td>\n",
       "      <td>-0.0087</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>op_setting2</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>2.930621e-04</td>\n",
       "      <td>-0.0006</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>op_setting3</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s1</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>518.670000</td>\n",
       "      <td>6.537152e-11</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "      <td>518.6700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s2</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>642.680934</td>\n",
       "      <td>5.000533e-01</td>\n",
       "      <td>641.2100</td>\n",
       "      <td>642.3250</td>\n",
       "      <td>642.6400</td>\n",
       "      <td>643.0000</td>\n",
       "      <td>644.5300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s3</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>1590.523119</td>\n",
       "      <td>6.131150e+00</td>\n",
       "      <td>1571.0400</td>\n",
       "      <td>1586.2600</td>\n",
       "      <td>1590.1000</td>\n",
       "      <td>1594.3800</td>\n",
       "      <td>1616.9100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s4</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>1408.933782</td>\n",
       "      <td>9.000605e+00</td>\n",
       "      <td>1382.2500</td>\n",
       "      <td>1402.3600</td>\n",
       "      <td>1408.0400</td>\n",
       "      <td>1414.5550</td>\n",
       "      <td>1441.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s5</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>14.620000</td>\n",
       "      <td>3.394700e-12</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "      <td>14.6200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s6</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>21.609803</td>\n",
       "      <td>1.388985e-03</td>\n",
       "      <td>21.6000</td>\n",
       "      <td>21.6100</td>\n",
       "      <td>21.6100</td>\n",
       "      <td>21.6100</td>\n",
       "      <td>21.6100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s7</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>553.367711</td>\n",
       "      <td>8.850923e-01</td>\n",
       "      <td>549.8500</td>\n",
       "      <td>552.8100</td>\n",
       "      <td>553.4400</td>\n",
       "      <td>554.0100</td>\n",
       "      <td>556.0600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s8</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>2388.096652</td>\n",
       "      <td>7.098548e-02</td>\n",
       "      <td>2387.9000</td>\n",
       "      <td>2388.0500</td>\n",
       "      <td>2388.0900</td>\n",
       "      <td>2388.1400</td>\n",
       "      <td>2388.5600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s9</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>9065.242941</td>\n",
       "      <td>2.208288e+01</td>\n",
       "      <td>9021.7300</td>\n",
       "      <td>9053.1000</td>\n",
       "      <td>9060.6600</td>\n",
       "      <td>9069.4200</td>\n",
       "      <td>9244.5900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s10</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>1.300000</td>\n",
       "      <td>4.660829e-13</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "      <td>1.3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s11</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>47.541168</td>\n",
       "      <td>2.670874e-01</td>\n",
       "      <td>46.8500</td>\n",
       "      <td>47.3500</td>\n",
       "      <td>47.5100</td>\n",
       "      <td>47.7000</td>\n",
       "      <td>48.5300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s12</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>521.413470</td>\n",
       "      <td>7.375534e-01</td>\n",
       "      <td>518.6900</td>\n",
       "      <td>520.9600</td>\n",
       "      <td>521.4800</td>\n",
       "      <td>521.9500</td>\n",
       "      <td>523.3800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s13</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>2388.096152</td>\n",
       "      <td>7.191892e-02</td>\n",
       "      <td>2387.8800</td>\n",
       "      <td>2388.0400</td>\n",
       "      <td>2388.0900</td>\n",
       "      <td>2388.1400</td>\n",
       "      <td>2388.5600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s14</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>8143.752722</td>\n",
       "      <td>1.907618e+01</td>\n",
       "      <td>8099.9400</td>\n",
       "      <td>8133.2450</td>\n",
       "      <td>8140.5400</td>\n",
       "      <td>8148.3100</td>\n",
       "      <td>8293.7200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s15</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>8.442146</td>\n",
       "      <td>3.750504e-02</td>\n",
       "      <td>8.3249</td>\n",
       "      <td>8.4149</td>\n",
       "      <td>8.4389</td>\n",
       "      <td>8.4656</td>\n",
       "      <td>8.5848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s16</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>1.556432e-14</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s17</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>393.210654</td>\n",
       "      <td>1.548763e+00</td>\n",
       "      <td>388.0000</td>\n",
       "      <td>392.0000</td>\n",
       "      <td>393.0000</td>\n",
       "      <td>394.0000</td>\n",
       "      <td>400.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s18</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>2388.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "      <td>2388.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s19</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s20</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>38.816271</td>\n",
       "      <td>1.807464e-01</td>\n",
       "      <td>38.1400</td>\n",
       "      <td>38.7000</td>\n",
       "      <td>38.8300</td>\n",
       "      <td>38.9500</td>\n",
       "      <td>39.4300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s21</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>23.289705</td>\n",
       "      <td>1.082509e-01</td>\n",
       "      <td>22.8942</td>\n",
       "      <td>23.2218</td>\n",
       "      <td>23.2979</td>\n",
       "      <td>23.3668</td>\n",
       "      <td>23.6184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_cycles</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>216.615724</td>\n",
       "      <td>5.002860e+01</td>\n",
       "      <td>128.0000</td>\n",
       "      <td>185.0000</td>\n",
       "      <td>207.0000</td>\n",
       "      <td>240.0000</td>\n",
       "      <td>362.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUL</th>\n",
       "      <td>20631.0</td>\n",
       "      <td>107.807862</td>\n",
       "      <td>6.888099e+01</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>51.0000</td>\n",
       "      <td>103.0000</td>\n",
       "      <td>155.0000</td>\n",
       "      <td>361.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count         mean           std        min        25%  \\\n",
       "unit          20631.0    51.506568  2.922763e+01     1.0000    26.0000   \n",
       "cycle         20631.0   108.807862  6.888099e+01     1.0000    52.0000   \n",
       "op_setting1   20631.0    -0.000009  2.187313e-03    -0.0087    -0.0015   \n",
       "op_setting2   20631.0     0.000002  2.930621e-04    -0.0006    -0.0002   \n",
       "op_setting3   20631.0   100.000000  0.000000e+00   100.0000   100.0000   \n",
       "s1            20631.0   518.670000  6.537152e-11   518.6700   518.6700   \n",
       "s2            20631.0   642.680934  5.000533e-01   641.2100   642.3250   \n",
       "s3            20631.0  1590.523119  6.131150e+00  1571.0400  1586.2600   \n",
       "s4            20631.0  1408.933782  9.000605e+00  1382.2500  1402.3600   \n",
       "s5            20631.0    14.620000  3.394700e-12    14.6200    14.6200   \n",
       "s6            20631.0    21.609803  1.388985e-03    21.6000    21.6100   \n",
       "s7            20631.0   553.367711  8.850923e-01   549.8500   552.8100   \n",
       "s8            20631.0  2388.096652  7.098548e-02  2387.9000  2388.0500   \n",
       "s9            20631.0  9065.242941  2.208288e+01  9021.7300  9053.1000   \n",
       "s10           20631.0     1.300000  4.660829e-13     1.3000     1.3000   \n",
       "s11           20631.0    47.541168  2.670874e-01    46.8500    47.3500   \n",
       "s12           20631.0   521.413470  7.375534e-01   518.6900   520.9600   \n",
       "s13           20631.0  2388.096152  7.191892e-02  2387.8800  2388.0400   \n",
       "s14           20631.0  8143.752722  1.907618e+01  8099.9400  8133.2450   \n",
       "s15           20631.0     8.442146  3.750504e-02     8.3249     8.4149   \n",
       "s16           20631.0     0.030000  1.556432e-14     0.0300     0.0300   \n",
       "s17           20631.0   393.210654  1.548763e+00   388.0000   392.0000   \n",
       "s18           20631.0  2388.000000  0.000000e+00  2388.0000  2388.0000   \n",
       "s19           20631.0   100.000000  0.000000e+00   100.0000   100.0000   \n",
       "s20           20631.0    38.816271  1.807464e-01    38.1400    38.7000   \n",
       "s21           20631.0    23.289705  1.082509e-01    22.8942    23.2218   \n",
       "total_cycles  20631.0   216.615724  5.002860e+01   128.0000   185.0000   \n",
       "RUL           20631.0   107.807862  6.888099e+01     0.0000    51.0000   \n",
       "\n",
       "                    50%        75%        max  \n",
       "unit            52.0000    77.0000   100.0000  \n",
       "cycle          104.0000   156.0000   362.0000  \n",
       "op_setting1      0.0000     0.0015     0.0087  \n",
       "op_setting2      0.0000     0.0003     0.0006  \n",
       "op_setting3    100.0000   100.0000   100.0000  \n",
       "s1             518.6700   518.6700   518.6700  \n",
       "s2             642.6400   643.0000   644.5300  \n",
       "s3            1590.1000  1594.3800  1616.9100  \n",
       "s4            1408.0400  1414.5550  1441.4900  \n",
       "s5              14.6200    14.6200    14.6200  \n",
       "s6              21.6100    21.6100    21.6100  \n",
       "s7             553.4400   554.0100   556.0600  \n",
       "s8            2388.0900  2388.1400  2388.5600  \n",
       "s9            9060.6600  9069.4200  9244.5900  \n",
       "s10              1.3000     1.3000     1.3000  \n",
       "s11             47.5100    47.7000    48.5300  \n",
       "s12            521.4800   521.9500   523.3800  \n",
       "s13           2388.0900  2388.1400  2388.5600  \n",
       "s14           8140.5400  8148.3100  8293.7200  \n",
       "s15              8.4389     8.4656     8.5848  \n",
       "s16              0.0300     0.0300     0.0300  \n",
       "s17            393.0000   394.0000   400.0000  \n",
       "s18           2388.0000  2388.0000  2388.0000  \n",
       "s19            100.0000   100.0000   100.0000  \n",
       "s20             38.8300    38.9500    39.4300  \n",
       "s21             23.2979    23.3668    23.6184  \n",
       "total_cycles   207.0000   240.0000   362.0000  \n",
       "RUL            103.0000   155.0000   361.0000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_data.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll now generate some histograms to demonstrate the range of values per sensor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40e31e17f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "exp_data.hist(figsize = (30,20))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we'll plot a correlation matrix. A correlation matrix illustrates correlation coefficients between sets of features. Each feature in the matrix is correlated with each of the other features in the matrix. This enables us to see which pairs have the highest correlation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40dc1d82b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cov = exp_data.drop(columns=['unit',]).corr()\n",
    "fig = plt.figure(figsize = (15,15))\n",
    "\n",
    "mask = np.zeros_like(cov, dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "cmap = sb.diverging_palette(220, 10, as_cmap=True)\n",
    "\n",
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "sb.heatmap(cov, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next step we will undertake is to examine how we can reduce the dimensions of the data set by by removing irrelevant or redundant features. The goal here is to find a minimum set of attributes such that the resulting probability distribution of the data classes is as close as possible to the original distribution obtained using all attributes. The algorithm we will employ is a random forest regressor.\n",
    "\n",
    "The first step will be to normalize the data with the minmaxscaler. Normalization is done so that each attribute falls within the same range. This step helps ensure that attributes with large domains will not dominate attributes with smaller domains."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_data = exp_data.drop(['unit', 'cycle', 'total_cycles'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def select_feature(df):\n",
    "   print(\"extract feature\")\n",
    "\n",
    "   # separate into input and output variables\n",
    "   array = df.values\n",
    "   X = df.drop('RUL',axis=1)\n",
    "   y = df.RUL\n",
    "\n",
    "   # Scale the data set\n",
    "   scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "   x_transformed = scaler.fit_transform(X)\n",
    "\n",
    "   # perform feature selection\n",
    "   rfe = RFE(RandomForestRegressor(n_estimators=50, random_state=1), 4)\n",
    "   fit = rfe.fit(X, y)\n",
    "\n",
    "   # report selected features\n",
    "   print('Selected Features:')\n",
    "   names = df.columns.values[0:-1]\n",
    "   for i in range(len(fit.support_)):\n",
    "     if fit.support_[i]:\n",
    "         print(names[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extract feature\n",
      "Selected Features:\n",
      "s4\n",
      "s9\n",
      "s11\n",
      "s12\n"
     ]
    }
   ],
   "source": [
    "select_feature(feature_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we can see that the most important features are s4, s9, s11, and s12."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Preprocessing the data\n",
    "\n",
    "In the next stage, we will prepare the data for use in the regression models. We create a function (load_train_data) to prepare a training set using the Turbofan training data. We then prepare the test data using the function (load_test_data). We create another function (normalize) to remove attributes where the standard deviation is less than 0, as these have little or no predictive qualities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_train_data(data_set):\n",
    "    data = pd.read_csv(data_set, sep = ' ', header = None)\n",
    "    data = data[list(range(0, 26))]\n",
    "    data.rename(columns = {0 : 'unit', 1 : 'cycle'}, inplace = True)\n",
    "    \n",
    "    total_cycles = data.groupby(['unit']).agg({'cycle' : 'max'}).reset_index()\n",
    "    total_cycles.rename(columns = {'cycle' : 'total_cycles'}, inplace = True)\n",
    "    \n",
    "    data = data.merge(total_cycles, how = 'left', left_on = 'unit', right_on = 'unit')\n",
    "    data['RUL'] = data.apply(lambda r: int(r['total_cycles'] - r['cycle']), axis = 1)\n",
    "    \n",
    "    return data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_test_data(data_set):\n",
    "    data = pd.read_csv(data_set, sep = ' ', header = None)\n",
    "    data = data[list(range(0, 26))]\n",
    "    data.rename(columns = {0 : 'unit', 1 : 'cycle'}, inplace = True)\n",
    "    \n",
    "    total_cycles = data.groupby(['unit']).agg({'cycle' : 'max'}).reset_index()\n",
    "    total_cycles.rename(columns = {'cycle' : 'total_cycles'}, inplace = True)\n",
    "    \n",
    "    data = data.merge(total_cycles, how = 'left', left_on = 'unit', right_on = 'unit')\n",
    "    \n",
    "    RUL = pd.read_csv(streaming_body_6, sep = ' ', header = None)\n",
    "    RUL = RUL[list(range(0, 1))]\n",
    "    RUL['unit'] = list(range(1, len(RUL) + 1))\n",
    "    RUL.rename(columns = {0 : 'RUL'}, inplace = True)\n",
    "    \n",
    "    data = data.merge(RUL, how = 'left', left_on = 'unit', right_on = 'unit')\n",
    "    \n",
    "    data['total_cycles'] = data.apply(lambda r: int(r['total_cycles'] + r['RUL']), axis = 1)\n",
    "    data['RUL'] = data.apply(lambda r: int(r['total_cycles'] - r['cycle']), axis = 1)\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize(arr):\n",
    "    mean = np.mean(arr)\n",
    "    std = np.std(arr)\n",
    "    \n",
    "    return (arr - mean) / std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_score(RUL_real, RUL_pred):\n",
    "   d = RUL_pred - RUL_real\n",
    "   return np.sum(np.exp(d[d >= 0] / 10) - 1) + np.sum(np.exp(-1 * d[d < 0] / 13) - 1)\n",
    "\n",
    "def MSE(RUL_real, RUL_pred):\n",
    "   d = RUL_pred - RUL_real\n",
    "   return np.sqrt(np.sum(d ** 2)) / len(d)\n",
    "\n",
    "def MAE(RUL_real, RUL_pred):\n",
    "    return np.mean(np.abs(RUL_pred - RUL_real))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading the training and testing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = load_train_data(streaming_body_4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data = load_test_data(streaming_body_5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = list(range(2, 26))\n",
    "\n",
    "train_data[features] = train_data[features].apply(normalize, axis = 0)\n",
    "test_data[features] = test_data[features].apply(normalize, axis = 0)\n",
    "\n",
    "test_rows = test_data.groupby(['unit']).agg({'cycle' : max})\n",
    "test_rows = test_rows.reset_index()\n",
    "test_rows = test_rows.merge(test_data, how = 'left', left_on = ['unit', 'cycle'],\n",
    "                                                    right_on = ['unit', 'cycle'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = train_data['RUL'].values\n",
    "\n",
    "X_pred = test_rows[features].dropna(how = 'all', axis = 1)\n",
    "\n",
    "X = train_data[features].dropna(how = 'all', axis = 1)\n",
    "\n",
    "X = X.as_matrix()\n",
    "X_pred = X_pred.as_matrix()\n",
    "\n",
    "y_real = test_rows['RUL'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Neural Network Regression\n",
    "\n",
    "We train the model using a deep neural network regression algorithm called DNNRegressor, using TensorFlow. For more information about neural networks, see https://en.wikipedia.org/wiki/Neural_network. We set the hidden units to be 10, 15, and 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using default config.\n",
      "WARNING:tensorflow:Using temporary folder as model directory: /home/dsxuser/.tmp/tmpl_76tjik\n",
      "INFO:tensorflow:Using config: {'_keep_checkpoint_max': 5, '_save_checkpoints_steps': None, '_log_step_count_steps': 100, '_session_config': None, '_save_summary_steps': 100, '_save_checkpoints_secs': 600, '_keep_checkpoint_every_n_hours': 10000, '_model_dir': '/home/dsxuser/.tmp/tmpl_76tjik', '_tf_random_seed': 1}\n",
      "INFO:tensorflow:Create CheckpointSaverHook.\n",
      "INFO:tensorflow:Saving checkpoints for 1 into /home/dsxuser/.tmp/tmpl_76tjik/model.ckpt.\n",
      "INFO:tensorflow:loss = 2.0455e+06, step = 1\n",
      "INFO:tensorflow:Saving checkpoints for 100 into /home/dsxuser/.tmp/tmpl_76tjik/model.ckpt.\n",
      "INFO:tensorflow:Loss for final step: 153457.0.\n"
     ]
    }
   ],
   "source": [
    "feature_columns = [tf.feature_column.numeric_column(\"x\", shape = [17])]\n",
    "\n",
    "regressor = tf.estimator.DNNRegressor(feature_columns = feature_columns,\n",
    "                                      hidden_units    = [16, 31, 16])\n",
    "\n",
    "train_input_fn = tf.estimator.inputs.numpy_input_fn(x = {\"x\": X},\n",
    "                                                    y = np.array(y, dtype = np.int),\n",
    "                                                    num_epochs = None,\n",
    "                                                    shuffle = True)\n",
    "\n",
    "predict_input_fn = tf.estimator.inputs.numpy_input_fn(x = {\"x\": np.array(X_pred)},\n",
    "                                                      num_epochs = 1,\n",
    "                                                      shuffle = False)\n",
    "\n",
    "regressor.train(input_fn = train_input_fn, steps = 100)\n",
    "y_pred = regressor.predict(predict_input_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from /home/dsxuser/.tmp/tmpl_76tjik/model.ckpt-100\n"
     ]
    }
   ],
   "source": [
    "y_pred = [val for val in y_pred]\n",
    "y_pred = np.array(list(map(lambda x: x['predictions'][0], y_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40f107f9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows = 1, ncols = 1, figsize = (10, 4))\n",
    "\n",
    "axes.scatter(test_rows['cycle'], y_real, color = 'green', label = 'Real RUL', alpha = 0.7, s = 15)\n",
    "axes.scatter(test_rows['cycle'], y_pred, color = 'blue', label = 'Predicted RUL', alpha = 0.7, s = 15)\n",
    "axes.set_xlabel('Cycle')\n",
    "axes.set_ylabel('RUL [cycles]')\n",
    "axes.set_ylim([0, 250])\n",
    "axes.set_title('NNR - Difference')\n",
    "\n",
    "\n",
    "\n",
    "axes.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4130965940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.abs(y_real - y_pred), bins = 20, color='yellow')\n",
    "plt.xlabel('Absolute error [cycles]')\n",
    "plt.ylabel('Freq [-]')\n",
    "plt.title('NNR - Result Histogram')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average score per UUT: 38.4940003879\n",
      "Mean squared Error: 3.16507505206\n",
      "Median difference: 22.8037147522\n",
      "R2 Score 0.41989249882\n"
     ]
    }
   ],
   "source": [
    "print('Average score per UUT:', compute_score(y_real, y_pred) / 100)\n",
    "print('Mean squared Error:', MSE(y_real, y_pred))\n",
    "print('Median difference:', np.median(np.abs(y_real - y_pred)))\n",
    "print('R2 Score',  r2_score(y_real, y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Kernel Ridge Regression\n",
    "\n",
    "We will compare our neural network against a Kernel Ridge Regression model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "KRmodel = KernelRidge(alpha=1.0)\n",
    "KRmodel.fit(X, y)\n",
    "y_pred_kr = KRmodel.predict(X_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f410cb80278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows = 1, ncols = 1, figsize = (10, 4))\n",
    "\n",
    "axes.scatter(test_rows['cycle'], y_real, color = 'green', label = 'Real RUL', alpha = 0.7, s = 15)\n",
    "axes.scatter(test_rows['cycle'], y_pred_kr, color = 'blue', label = 'Predicted RUL', alpha = 0.7, s = 15)\n",
    "axes.set_xlabel('Cycle')\n",
    "axes.set_ylabel('RUL [cycles]')\n",
    "axes.set_ylim([0, 250])\n",
    "axes.set_title('KR - Difference')\n",
    "\n",
    "axes.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40dc205a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.abs(y_real - y_pred_kr), bins = 20, color='purple')\n",
    "plt.xlabel('Absolute error [cycles]')\n",
    "plt.ylabel('Freq [-]')\n",
    "plt.title('KR - Result Histogram')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average score per UUT: 869890.05872\n",
      "Mean squared Error: 13.2596990912\n",
      "Median difference: 128.841114882\n",
      "R2 Score -9.18140686412\n"
     ]
    }
   ],
   "source": [
    "print('Average score per UUT:', compute_score(y_real, y_pred_kr) / 100)\n",
    "print('Mean squared Error:', MSE(y_real, y_pred_kr))\n",
    "print('Median difference:', np.median(np.abs(y_real - y_pred_kr)))\n",
    "print('R2 Score',  r2_score(y_real, y_pred_kr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Random Forest Regression\n",
    "Finally we compare against Random Forest Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfr = RandomForestRegressor()\n",
    "rfr.fit(X, y)\n",
    "y_pred_rfr = rfr.predict(X_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40d7340b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows = 1, ncols = 1, figsize = (10, 4))\n",
    "\n",
    "axes.scatter(test_rows['cycle'], y_real, color = 'red', label = 'Real RUL', alpha = 0.7, s = 15)\n",
    "axes.scatter(test_rows['cycle'], y_pred_rfr, color = 'blue', label = 'Predicted RUL', alpha = 0.7, s = 15)\n",
    "axes.set_xlabel('Cycle')\n",
    "axes.set_ylabel('RUL [cycles]')\n",
    "axes.set_ylim([0, 250])\n",
    "axes.set_title('RandomForest - Difference')\n",
    "\n",
    "\n",
    "axes.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f410cb2bb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.abs(y_real - y_pred_rfr), bins = 20, color='green')\n",
    "plt.xlabel('Absolute error [cycles]')\n",
    "plt.ylabel('Freq [-]')\n",
    "plt.title('RandomForest - Result Histogram')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average score per UUT: 161.79509668\n",
      "Mean squared Error: 3.58811231708\n",
      "Median difference: 24.5\n",
      "R2 Score 0.254457313974\n"
     ]
    }
   ],
   "source": [
    "print('Average score per UUT:', compute_score(y_real, y_pred_rfr) / 100)\n",
    "print('Mean squared Error:', MSE(y_real, y_pred_rfr))\n",
    "print('Median difference:', np.median(np.abs(y_real - y_pred_rfr)))\n",
    "print('R2 Score',  r2_score(y_real, y_pred_rfr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "For evaluation purposes, we employed several techniques:\n",
    "\n",
    "* R2. This is the coefficient of determination. It provides a measure of how well future samples are likely to be predicted by the model. The best possible score is 1.0 and it can be negative (because the model can be arbitrarily worse).  \n",
    "* MSE. This is the mean square error, a risk metric corresponding to the expected value of the squared (quadratic) error or loss. Values closer to 0 are best.\n",
    "* Median Difference. This is median of absolute differences between the real and predicted RULs\n",
    "* Average Score. This is the overall score divided by the number of testing samples.\n",
    "\n",
    "When we examine all three models, we can see that the Neural Network was the best, outperforming Kernel Ridge and Random Forest on all evaluations. Although the evaluation scores are not terrific, bear in mind that we did minimal data preprocessing and we did not tune the models. We would expect significant improvements were we to work with the data and the models more, but that is outside the scope of this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40dc11e8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows = 1, ncols = 3, figsize = (15, 4))\n",
    "axes[0].hist(np.abs(y_real - y_pred), bins = 20, color='yellow')\n",
    "axes[0].set_xlabel('Absolute error [cycles]')\n",
    "axes[0].set_ylabel('Freq [-]')\n",
    "axes[0].set_title('NNR - Result Histogram')\n",
    "\n",
    "axes[1].hist(np.abs(y_real - y_pred_kr), bins = 20, color='purple')\n",
    "axes[1].set_xlabel('Absolute error [cycles]')\n",
    "axes[1].set_ylabel('Freq [-]')\n",
    "axes[1].set_title('KR - Result Histogram')\n",
    "\n",
    "axes[2].hist(np.abs(y_real - y_pred_rfr), bins = 20, color='green')\n",
    "axes[2].set_xlabel('Absolute error [cycles]')\n",
    "axes[2].set_ylabel('Freq [-]')\n",
    "axes[2].set_title('RandomForest - Result Histogram')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Evaluator         | Neural Network| Kernel Ridge| Random Forest|\n",
    "| ----------------- |:-------------:|:-----------:|-------------:|\n",
    "| Average Score     | 38.49         | 869890.06      |161.80         |\n",
    "| MSE               | 3.17          | 13.25        |3.59         |\n",
    "| Median Difference | 22.8         | 128.84       |24.5        |\n",
    "| R2 Score          | 0.42          | -9.18        |0.25         |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hopefully, this notebook has give you a sense of the various steps one might take in a regression modelling excercise. Finding the best fit for the problem you are trying to solve is iterative and experimental.\n",
    "\n",
    "Now that you have found a good model for this type of regression, think about how you might use this in a production setting with Maximo Predictive Maintenance Insights (PMI). For example, in addition to viewing it in Maximo PMI, you might also want to create some automation scripts to trigger service requests or even work orders when a predicted RUL is closer than expected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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