EESI / PyFeastLinks
A Python interface to the Feature Selection Toolkit, contains JMI, BetaGamma, CMIM, CondMI, DISR, ICAP, and mRMR
☆19Updated 11 years ago
Alternatives and similar repositories for PyFeast
Users that are interested in PyFeast are comparing it to the libraries listed below
Sorting:
- A FEAture Selection Toolbox for C/C+, Java, and Matlab/Octave.☆72Updated 3 years ago
- Robust Ensemble of SVMs☆21Updated 11 years ago
- Randomized output tree for multilabel / multi-output regression tasks☆23Updated 10 years ago
- Initial attempt to incorporate some time-series analysis features from hctsa into python land☆28Updated 9 years ago
- Multilayer Perceptron Keras wrapper for sklearn☆69Updated 3 years ago
- scikit-fusion: Data fusion via collective latent factor models☆150Updated 2 years ago
- ☆68Updated this week
- Code for ensemble clustering☆102Updated 7 months ago
- Original implementation of Calibrated Boosting-Forest☆18Updated 8 years ago
- An improved implementation of the classical feature selection method: minimum Redundancy and Maximum Relevance (mRMR).☆83Updated 3 years ago
- Self-Organizing Map for unsupervised feature engineering and dimensionality reduction☆21Updated 12 years ago
- ☆74Updated 6 years ago
- Code for the Kaggle Marinexplore challenge☆17Updated 12 years ago
- Denoising Autoencoders for Phenotype Stratification☆42Updated 7 years ago
- Master's project - Artificial Immune System for symbolic regression.☆14Updated 12 years ago
- Variational Bayesian Mixture of Factor Analysers☆24Updated 10 years ago
- Run Nx2 Cross Validation for multiple binary classifiers in parallel with optional downsampling☆13Updated 10 years ago
- Bayesian Neural Networks☆43Updated 10 years ago
- A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.☆125Updated 6 months ago
- An implementation of Deep Linear Discriminant Analysis (DeepLDA) in Keras☆41Updated 7 years ago
- minimum Redundancy Maximum Relevance☆21Updated 13 years ago
- Amino-Acid Sequence Annotation Predictor (ASAP)