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This package includes a scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning. These Relief-Based algorithms (RBAs) are designed for feature weighting/selection as part of a machine learning pipeline (supervised learning). Presently this includes the following core RBAs: ReliefF, SURF, SURF*, MultiSURF*, and MultiSURF. Additionally, an implementation of the iterative TuRF mechanism and VLSRelief is included. WWW: https://github.com/EpistasisLab/scikit-rebate
10 lines
541 B
Plaintext
10 lines
541 B
Plaintext
This package includes a scikit-learn-compatible Python implementation of ReBATE,
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a suite of Relief-based feature selection algorithms for Machine Learning. These
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Relief-Based algorithms (RBAs) are designed for feature weighting/selection as
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part of a machine learning pipeline (supervised learning). Presently this
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includes the following core RBAs: ReliefF, SURF, SURF*, MultiSURF*, and
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MultiSURF. Additionally, an implementation of the iterative TuRF mechanism and
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VLSRelief is included.
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WWW: https://github.com/EpistasisLab/scikit-rebate
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