Toolbox for Bayesian Optimization and Model-Based Optimization in R
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Updated
Sep 14, 2023 - R
Toolbox for Bayesian Optimization and Model-Based Optimization in R
Hyperparameter optimization package of the mlr3 ecosystem
Flexible Bayesian Optimization in R
Black-box optimization framework for R.
A simple collection of well working NLP models (Keras, H2O, StarSpace) tuned and benchmarked on a variety of datasets.
Reticulate wrapper for hyperopt
An extensible framework for reproducible machine learning experiments
The main objective of this project is to build a model to identify whether the delivery of an order will be late or on time.
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models
This project predicts diabetes using Decision Trees and Random Forest algorithms. It optimizes models with hyperparameter tuning and evaluates performance through accuracy, sensitivity, specificity, and F1 score. Random Forest outperforms Decision Trees, effectively addressing class imbalance.
The supervisor repo for task 2 of the "Analyzing Big Data Laboratory Course" at the Karlsruhe Institute of Technology (KIT), summer term 2019.
Analysis music on Spotify and predictions of preferences
A data mining project that encompass Machine Learning in predicting Patient Survivability, This project is built as a fulfillment for my masters degree.
Imbalanced classification with loan clients dataset.
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