hlin117 / mdlp-discretizationLinks
An implementation of the minimum description length principal expert binning algorithm by Usama Fayyad
☆105Updated 2 years ago
Alternatives and similar repositories for mdlp-discretization
Users that are interested in mdlp-discretization are comparing it to the libraries listed below
Sorting:
- Discretization with Fayyad and Irani's minimum description length principle criterion (MDLPC)☆60Updated 6 years ago
- CostSensitiveClassification Library in Python☆208Updated 4 years ago
- A library for factorization machines and polynomial networks for classification and regression in Python.☆245Updated 4 years ago
- Library for machine learning stacking generalization.☆117Updated 6 years ago
- scikit-learn compatible implementation of stability selection.☆212Updated 2 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆39Updated 3 years ago
- ☆34Updated 8 years ago
- Extension of the awesome XGBoost to linear models at the leaves☆78Updated 5 years ago
- Scikit-learn compatible implementations of the Random Rotation Ensemble idea of (Blaser & Fryzlewicz, 2016)☆43Updated 9 years ago
- Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one…☆381Updated 3 years ago
- A fast xgboost feature selection algorithm☆222Updated 4 years ago
- A simple, extensible library for developing AutoML systems☆175Updated last year
- A density ratio estimator package for python using the KLIEP algorithm.☆107Updated 4 years ago
- A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.☆418Updated 2 years ago
- (Python, R) Cost-sensitive multiclass classification (Weighted-All-Pairs, Filter-Tree & others)☆48Updated 3 weeks ago
- An improved implementation of the classical feature selection method: minimum Redundancy and Maximum Relevance (mRMR).☆83Updated 3 years ago
- Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"☆67Updated last year
- Bayesian Optimization using xgboost and sklearn API☆226Updated 9 years ago
- XGBoost Feature Interactions Reshaped☆429Updated 7 years ago
- Tutorial on cost-sensitive boosting and calibrated AdaMEC.☆26Updated 8 years ago
- Analysis of Categorical Encodings for dense Decision Trees☆41Updated 8 years ago
- Python implementation of stacked generalization classifier. Plays nice with sklearn.☆71Updated 8 years ago
- An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.☆82Updated 3 years ago
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆69Updated last month
- Python code for tree ensemble interpretation☆84Updated 4 years ago
- ☆34Updated 6 years ago
- Minimum description length principle algorithm in Python, for optimal binning of continuous variables☆60Updated 2 years ago
- A scikit-learn compatible implementation of hyperband☆76Updated 5 years ago
- ☆60Updated 6 years ago
- Hierarchical Time Series Forecasting using Prophet☆144Updated 4 years ago