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