A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
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Feature engineering and selection open-source Python library compatible with sklearn.
Machine Learning in R
- machine-learning
- data-science
- tuning
- cran
Python implementations of the Boruta all-relevant feature selection method.
open-source feature selection repository in python
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
- feature-selection
- data-science
- python
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
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.
- machine-learning
- python
- evolutionary-algorithms
- genetic-algorithm
A fast xgboost feature selection algorithm
- machine-learning
- machine-learning-algorithms
- feature-selection
- xgboost-algorithm
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.
- svm
- regression
- classification
- machine-learning
GNN-based gene-selection deep learning model for drug response prediction