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Genetic feature selection module for scikit-learn
The main features of manuel-calzolari/sklearn-genetic are: Evolutionary Algorithms, Feature Selection.
Projects with overlapping indexed features include: rhiever/data-analysis-and-machine-learning-projects — This is a collection of machine learning projects, data visualization portfolios, and predictive analytics tools. The… astrazeneca/subtab. chasedehan/boostaroota — A fast xgboost feature selection algorithm. deap/deap. efavdb/linselect. aqibsaeed/genetic-cnn — CNN architecture exploration using Genetic Algorithm.
This is a collection of machine learning projects, data visualization portfolios, and predictive analytics tools. The repository provides implementation examples for training predictive models, executing data analysis pipelines, and estimating metadata values through historical statistical tables. The project emphasizes evolutionary computing, utilizing genetic algorithms and programming to solve optimization problems. This includes calculating the shortest distance between geographic coordinates and automating the selection of models and hyperparameters within machine learning pipelines. Ad
CNN architecture exploration using Genetic Algorithm
