df_model_monitoring_summary: Assess observed and expected feature distributions for drift.

In BrandonRCopeland/DataScience: Provides Helper Functions for Data Science Analysis

Assess observed and expected feature distributions for drift.

Description

This function will take a distribution table of observed and expected features and perform a Chi Square Goodness of Fit test for all numeric and categorical features. Furthermore, with will account for sample size and degrees of freedom by performing a subsequent Cramers V Goodness of Fit test.

Usage

df_model_monitoring_summary(distributions)

Arguments

distributions

Required: Distributions for the features. Can be created via the df_model_monitoring_distributions function.

Value

A base R dataframe containing the feature, # of bins, Chi Squared Value, P-Value, Cramer's V, Result, and Magnitude.

BrandonRCopeland/DataScience documentation built on Oct. 14, 2023, 9:45 a.m.