Addressing n<<p biology problems with interpretable random forest results via partial dependence plots. - Construction of an ideal high-density lipoprotein
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Nov 15, 2020
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partial-dependence-plots
Here are 7 public repositories matching this topic...
Partial-dependence plots on supervised-learning models
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Apr 28, 2020 - Jupyter Notebook
🎯📈 Sequantial and model-based optimization
machine-learning scikit-learn scientific-computing hyperparameter-optimization bayesopt global-optimization bayesian-optimization hyperparameter-tuning global-optimization-algorithms partial-dependence-plot blackbox-optimization surrogate-based-optimization scikit-optimize partial-dependence-plots sce-ua scipy-optimize
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Dec 21, 2024 - Python
Partial Dependencie Monitor, related to my theseiswork
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Feb 18, 2018 - HTML
little demo project on how to evaluate and interprete ordinal forests
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Sep 25, 2022 - R
This project aims to analyze and model the information retrieved by a real-world IoT system in order to understand which are the relationships in the dataset chosen between the dependent variables and the selected target feature. To help the understanding of the inner working of the models adopted, several machine learning interpretability techn…
exploratory-data-analysis regression internet-of-things ice lime random-forest-regression xgboost-regression shap partial-dependence-plots lightgbm-regressor surrogate-trees
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Mar 30, 2021 - Jupyter Notebook
Why do employees leave? This project first compares the predictive performance of three different models, then uses the best model to help reveal the top contributing factors.
machine-learning random-forest confusion-matrix logisitic-regression xgboost-model shapley-values one-hot-encoding permutation-importances partial-dependence-plots ordinal-encoding gini-importance
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May 24, 2022 - Jupyter Notebook
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