RFE/RFECV are not only feature selectors (SelectorMixin) but also classifiers/regressors (MetaEstimatorMixin), though ELI5 explainweights doesn't support them as classifiers/regressors. The final fit of an RFE/RFECV object is a fitted estimator with either `rfe.estimator.coeforrfe.estimator.featureimportances` and in sklearn you do not usually follow up RFE/RFECV with another classifier or regressor. Would be great if ELI5 could support metaestimators in explain_weights.
RFE/RFECV are not only feature selectors (SelectorMixin) but also classifiers/regressors (MetaEstimatorMixin), though ELI5 explainweights doesn't support them as classifiers/regressors. The final fit of an RFE/RFECV object is a fitted estimator with either `rfe.estimator.coef
orrfe.estimator.featureimportances` and in sklearn you do not usually follow up RFE/RFECV with another classifier or regressor. Would be great if ELI5 could support metaestimators in explain_weights.