casper-hansen / Nested-Cross-ValidationLinks
Nested cross-validation for unbiased predictions. Can be used with Scikit-Learn, XGBoost, Keras and LightGBM, or any other estimator that implements the scikit-learn interface.
☆64Updated 6 years ago
Alternatives and similar repositories for Nested-Cross-Validation
Users that are interested in Nested-Cross-Validation are comparing it to the libraries listed below
Sorting:
- xverse (XuniVerse) is collection of transformers for feature engineering and feature selection☆117Updated 2 years ago
- Python package for Imputation Methods☆251Updated last year
- Missing Data Imputation for Python☆248Updated last year
- Feature Selection for Clustering☆96Updated 7 years ago
- scikit-learn compatible implementation of stability selection.☆214Updated 2 years ago
- A fast xgboost feature selection algorithm☆228Updated 4 years ago
- How to Interpret SHAP Analyses: A Non-Technical Guide☆57Updated 4 years ago
- Repo for the ML_Insights python package☆153Updated 7 months ago
- A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.☆420Updated 2 years ago
- A scikit-learn compatible implementation of hyperband☆76Updated 6 years ago
- hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…☆64Updated 9 months ago
- Improving XGBoost survival analysis with embeddings and debiased estimators☆342Updated last year
- A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.☆64Updated last year
- Python implementation of Density-Based Clustering Validation☆177Updated last year
- Tutorial on survival analysis using TensorFlow.☆47Updated 5 years ago
- A power-full Shapley feature selection method.☆211Updated 2 months ago
- scikit-learn gradient-boosting-model interactions☆25Updated 2 years ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆90Updated last year
- Python Accumulated Local Effects package☆169Updated 2 years ago
- Genetic feature selection module for scikit-learn☆323Updated last year
- Open source package for Survival Analysis modeling☆367Updated last year
- PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in…☆140Updated 9 months ago
- TabNet for fastai☆124Updated 2 months ago
- Random Forest or XGBoost? It is Time to Explore LCE☆70Updated 2 years ago
- An updated (2025) guide to Deep Learning for tabular data, comparing a fine-tuned Keras 3 (PyTorch backend) DNN and an Optuna-optimized…☆47Updated 3 months ago
- All Relevant Feature Selection☆142Updated 8 months ago
- Better heatmaps in Python☆137Updated 4 years ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 3 years ago
- This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given datase…☆166Updated 2 years ago
- Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification☆97Updated last year