histcounts
Compute histogram bin counts for specified variables in baseline and target data for drift detection
Description
returns the histogram bin counts in the table H
= histcounts(DDiagnostics
)H
for the variables
specified for drift detection in the call to detectdrift
.
returns the bin counts for the variables specified by H
= histcounts(DDiagnostics
,Variables=variables
)variables
.
Examples
Input Arguments
Output Arguments
Algorithms
For categorical data,
detectdrift
adds 0.5 correction factor to histogram bin counts for each bin to handle empty bins (categories). This is equivalent to the assumption that the parameter p, probability that value of the variable would be in that category, has the prior distribution Beta(0.5,0.5), i.e. Jefferys prior assumption for the distribution parameter.histcounts
treats a variable as ordinal for visualization purposes under any of the following cases:If the variable is ordinal in either baseline or target data and the categories from baseline and target data are the same.
If the variable is ordinal in either in baseline or target data and the categories of the other data set is a subset of the ordinal data.
If the variable is ordinal in both baseline and target data and categories from either one is a subset of the other.
If a variable is ordinal,
histcounts
preserves the order of the bin names.
Version History
See Also
detectdrift
| DriftDiagnostics
| plotDriftStatus
| plotEmpiricalCDF
| plotHistogram
| plotPermutationResults
| ecdf
| summary