Nature-inspired algorithms for hyper-parameter tuning of Scikit-Learn models.
MIT License
Python package for the GenSVM classifier
SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-co...
Implementations of the machine learning algorithm with Python and numpy
Machine learning's parameter search and feature selection module which is integrated log managem...
scikit-activeml: Python library for active learning on top of scikit-learn
Python implementations of the Boruta all-relevant feature selection method.
This library allows you to quickly train machine learning classifiers by automatically splitting ...
Machine Learning Tutor Python library
Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).
Implementation of Open-Set Likelihood Maximization for Few-Shot Learning
Constructing decision trees with genetic algorithm with a scikit-learn inspired API
A scikit-learn wrapper for HpBandSter hyper parameter search.
ML hyperparameters tuning and features selection, using evolutionary algorithms.
A constantly updated python machine learning cheatsheet