sklearn_explain: This is an experimental tool that gives model individual score explanation for an already trained scikit-learn model. Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score. These predictors can then be ranked according to their contribution in the final score (leading to a positive or negative decision). sklearn_explain is developed and tested using a python 3.5 version
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References in zbMATH (referenced in 1 article )
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- Hubert Baniecki; Przemyslaw Biecek: modelStudio: Interactive Studio with Explanations for ML Predictive Models (2019) not zbMATH