Detecting positivity violations in multidimensional data
Abstract:
An example computer-implemented method includes receiving, via a processor, a dataset of objects to be tested for positivity violations. The method includes generating, via the processor, a feature matrix based on features extracted from the objects. The method also includes generating, via the processor, decision trees to group the objects into homogenous groups based on entropy and generate a random forest to compute consistency of violations. The method further includes detecting, via the processor, a positivity violation based on an entropy threshold, a consistency threshold, and a statistical significance threshold being exceeded. The method further includes generating, via the processor, an interactive representation to display the positivity violation.
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