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RobustmRMR: a ensemble framework based on mRMR for feature selection. RedundancyThresholdSurv: group features and select one feature with the best performance from each group

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ensembled-mRMR-feature-selection

RobustmRMR: a ensemble framework based on mRMR for feature selection.

RedundancyThresholdSurv: group features and select one feature with the best performance from each group.

note: place redundancy_threshold_surv.py file in the directory of /xxx/python3.6/site-packages/sklearn/feature_selection/ and modify the "init.py" file in the same directory.

Prerequisites:

Python3

Numpy

Pandas

Scikit-learn

Scikit-feature

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RobustmRMR: a ensemble framework based on mRMR for feature selection. RedundancyThresholdSurv: group features and select one feature with the best performance from each group

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