Merge pull request #3 from hoanglinh171/lu

Lu
hoanglinh171 · Jan 26, 2022 · 91efc00 · 91efc00
2 parents 7b90192 + bfc6822
commit 91efc00
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diff --git a/content/lectures/lecture05/notebook/s1-exa2-challenge.ipynb b/content/lectures/lecture05/notebook/s1-exa2-challenge.ipynb
@@ -492,7 +492,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -506,7 +506,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/content/lectures/lecture05/notebook/s1-exb1-challenge.ipynb b/content/lectures/lecture05/notebook/s1-exb1-challenge.ipynb
diff --git a/content/lectures/lecture06/notebook/s1-exc1-challenge.ipynb b/content/lectures/lecture06/notebook/s1-exc1-challenge.ipynb
diff --git a/content/lectures/lecture06/notebook/s1-exc2-challenge.ipynb b/content/lectures/lecture06/notebook/s1-exc2-challenge.ipynb
diff --git a/content/lectures/lecture06/notebook/s1-exc3-challenge.ipynb b/content/lectures/lecture06/notebook/s1-exc3-challenge.ipynb
diff --git a/content/lectures/lecture06/notebook/s2-exa1-challenge.ipynb b/content/lectures/lecture06/notebook/s2-exa1-challenge.ipynb
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -108,35 +108,35 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
+       "      <td>0</td>\n",
        "      <td>230.1</td>\n",
        "      <td>37.8</td>\n",
        "      <td>69.2</td>\n",
        "      <td>22.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <td>1</td>\n",
        "      <td>44.5</td>\n",
        "      <td>39.3</td>\n",
        "      <td>45.1</td>\n",
        "      <td>10.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <td>2</td>\n",
        "      <td>17.2</td>\n",
        "      <td>45.9</td>\n",
        "      <td>69.3</td>\n",
        "      <td>9.3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
+       "      <td>3</td>\n",
        "      <td>151.5</td>\n",
        "      <td>41.3</td>\n",
        "      <td>58.5</td>\n",
        "      <td>18.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
+       "      <td>4</td>\n",
        "      <td>180.8</td>\n",
        "      <td>10.8</td>\n",
        "      <td>58.4</td>\n",
@@ -155,7 +155,7 @@
        "4  180.8   10.8       58.4   12.9"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -174,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -187,29 +187,29 @@
     "\n",
     "for i in cols:\n",
     "    #Set each of the predictors from the previous list as x\n",
-    "    x = df[___]\n",
+    "    x = df[i]\n",
     "    \n",
     "    \n",
     "    #\"Sales\" column is the reponse variable\n",
-    "    y = df[___]\n",
+    "    y = df[\"Sales\"]\n",
     "    \n",
     "   \n",
     "    #Splitting the data into train-test sets with 80% training data and 20% testing data. \n",
     "    #Set random_state as 0\n",
-    "    xtrain, xtest, ytrain, ytest = train_test_split(___)\n",
+    "    xtrain, xtest, ytrain, ytest = train_test_split(x, y, train_size=0.8, random_state=42)\n",
     "\n",
     "    #Create a LinearRegression object and fit the model\n",
     "    lreg = LinearRegression()\n",
-    "    lreg.fit(___)\n",
+    "    lreg.fit(xtrain, ytrain)\n",
     "    \n",
     "    #Predict the response variable for the test set\n",
-    "    y_pred= lreg.predict(___)\n",
+    "    y_pred= lreg.predict(xtest)\n",
     "    \n",
     "    #Compute the MSE\n",
-    "    MSE = mean_squared_error(___)\n",
+    "    MSE = mean_squared_error(ytest, y_pred)\n",
     "    \n",
     "    #Append the MSE to the list\n",
-    "    mse_list.append(___)\n"
+    "    mse_list.append(MSE)\n"
    ]
   },
   {
@@ -221,9 +221,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "+------------------------------+--------------------+\n",
+      "|          Predictors          |        MSE         |\n",
+      "+------------------------------+--------------------+\n",
+      "|            ['TV']            | 10.204654118800956 |\n",
+      "|          ['Radio']           | 23.248766588129108 |\n",
+      "|        ['Newspaper']         | 30.620733995242563 |\n",
+      "|       ['TV', 'Radio']        | 3.137948009068354  |\n",
+      "|     ['TV', 'Newspaper']      | 11.062557300662816 |\n",
+      "|    ['Radio', 'Newspaper']    |  23.2046437454446  |\n",
+      "| ['TV', 'Radio', 'Newspaper'] | 3.174097353976104  |\n",
+      "+------------------------------+--------------------+\n"
+     ]
+    }
+   ],
    "source": [
     "t = PrettyTable(['Predictors', 'MSE'])\n",
     "\n",
@@ -244,9 +262,7 @@
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "#### Your answer here"
-   ]
+   "source": []
   }
  ],
  "metadata": {
@@ -265,7 +281,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,