Data Exploration with Information Theory (Weight-of-Evidence and
Information Value)
person("Larsen", "Kim", email = "kblarsen4@gmail.com", role = c("aut", "cre"))
Performs exploratory data analysis and variable screening for binary classification models using weight-of-evidence (WOE) and information value (IV). In order to make the package as efficient as possible, aggregations are done in data.table and creation of WOE vectors can be distributed across multiple cores. The package also supports exploration for uplift models (NWOE and NIV).
data.table, ggplot2, grid, plyr, iterators, doParallel,
parallel, foreach

data.table, ggplot2, grid, plyr, utils, iterators, doParallel,
parallel, foreach

Performs exploratory data analysis and variable screening for
binary classification models using weight-of-evidence (WOE) and information
value (IV). In order to make the package as efficient as possible, aggregations
are done in data.table and creation of WOE vectors can be distributed across
multiple cores. The package also supports exploration for uplift models (NWOE
and NIV).

Performance Analysis and Companion Functions for Binary
Classification Problems
Provides companion function for analysing the performance of classification models. Plot 'ROC' Curve in 'ggplot2', 'AUROC', 'IV', 'WOE' Calculation for Binary Classification.

Performance Analysis and Companion Functions for Accuracy
Improvement for Binary Classification Problems
Provides companion function for analysing the performance of classification models. Also, provides function to optimise probability cut-off score based on used specified objectives, Plot 'ROC' Curve in 'ggplot2', 'AUROC', 'IV', 'WOE' Calculation, etc to aid accuracy improvement in binary classification models.
https://github.com/selva86/InformationValue/issues License:
GPL (>= 2)

Performance Analysis and Companion Functions for Binary
Classification Models
Provides companion function for analysing the performance of classification models. Also, provides function to optimise probability cut-off score based on used specified objectives, Plot 'ROC' Curve in 'ggplot2', 'AUROC', 'IV', 'WOE' Calculation, 'KS Statistic' etc to aid accuracy improvement in binary classification models.