REP (Reproducible Experiment Platform) library provides functionality for all your basic needs to deal with machine learning.
It includes:
- Data support different data transformations, including operations in memory and on the disk
- Estimators (classification and regression) is sklearn-like wrappers for variety of machine learning libraries implementations (Sklearn, Uboost, XGBoost, TMVA). You can use them as base estimators in sklearn
- Meta Machine Learning contains factory (the set of estimators), grid search, folding algorithm. Also parallel execution on a cluster is supported
- Report for models contains helpful classes to get model result information on any dataset
- Plotting is wrapper for different plotting libraries including interactive plots (matplotlib, bokeh, tmva, plotly)
- Utilities contains additional functions