Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
created at Sept. 4, 2015, 4:33 p.m.
An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
created at Sept. 5, 2022, 4:29 p.m.
A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engineering ðŸ›
created at Sept. 18, 2022, 1:52 p.m.
TensorLight - A high-level framework for TensorFlow
created at Oct. 19, 2016, 2:35 p.m.
Scikit-learn compatible wrapper of the Random Bits Forest program written by (Wang et al., 2016)
created at July 31, 2016, 3:17 p.m.
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
created at July 11, 2020, 8:33 a.m.
Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University
created at July 9, 2018, 1:44 p.m.
ML hyperparameters tuning and features selection, using evolutionary algorithms.
created at Jan. 18, 2020, 7:16 p.m.
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
created at June 22, 2017, 7:41 p.m.
Auralisation of learned features in CNN (for audio)
created at Dec. 4, 2015, 3 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.
created at April 22, 2017, 10:16 p.m.
⬛ Python Individual Conditional Expectation Plot Toolbox
created at Dec. 2, 2015, 3:49 p.m.
A strongly-typed genetic programming framework for Python
created at Jan. 18, 2017, 8:11 p.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
created at Sept. 18, 2019, 5:58 p.m.