KNIME Machine Learning Interpretability Extension version 4.3.0.v202011191524 by KNIME AG, Zurich, Switzerland
Calculates the SHAP values by evaluating the predictions your model made in the loop body. For each explained row of interest (rows in the first input table of the SHAP Loop Start node, we will refer to these as ROI), the output table of this node contains d rows where d is the number of predictions your model produces (e.g. one for each class probability in a classification task). The rows consist of four special columns followed by a column for each of your features that hold the SHAP value of that feature for the current prediction column. The special columns are:
To use this node in KNIME, install KNIME Machine Learning Interpretability Extension from the following update site:
A zipped version of the software site can be downloaded here.
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