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
Music discovery tool that provides recommendations based on selected Lidarr artists, using Spotify or LastFM.
Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang
- go
- golang
- natural-language-processing
- nlp
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
A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by
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
Visually Validate Playwright Tests Without Flaky Selectors
GNN-based gene-selection deep learning model for drug response prediction