A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
updated at Sept. 22, 2024, 5:06 p.m.
Auralisation of learned features in CNN (for audio)
updated at Sept. 10, 2024, 4:38 a.m.
scikit-learn inspired API for CRFsuite
updated at Aug. 30, 2024, 12:15 p.m.
A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
updated at Aug. 21, 2024, 12:07 p.m.
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
updated at Aug. 18, 2024, 4:46 p.m.
Directions overlay for working with pandas in an analysis environment
updated at July 8, 2024, 7:18 p.m.
A library that implements fairness-aware machine learning algorithms
updated at July 3, 2024, 4:26 a.m.
The goal of pandas-log is to provide feedback about basic pandas operations. It provides simple wrapper functions for the most common functions that add additional logs
updated at May 1, 2024, 3:55 a.m.
SigOpt wrappers for scikit-learn methods
updated at April 29, 2024, 9:26 p.m.
A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engineering ðŸ›
updated at April 18, 2024, 8:08 a.m.
Universal 1d/2d data containers with Transformers functionality for data analysis.
updated at March 15, 2024, 9:16 a.m.