calculateBinaryMI: Calculates multiple 2 class mutual information scores from...
In terminological/tidy-info-stats: Functions for manipulating information statistics
View source: R/tidyBinaryInfoStats.R
calculateBinaryMI R Documentation
Calculates multiple 2 class mutual information scores from confusion matrix probabilities in dplyr friendly manner
Description
The purpose of this is to make it possible to calculate MI in a DBPLYR sql table
Usage
calculateBinaryMI(df)
Arguments
df
a dataframe containing one observation per row & full confusion matrix and marginal probabilities: i.e. p_x1, p_x0, p_y1, p_y0, p_x1y1, p_x0y1, p_x1y0, and p_x0y0 columns (see probabilitiesFromCounts)
Value
the datatable with additional columns for entropy, mutual information, pointwise mutual information and normalised pointwise mutual information for all various combinations of outcome
terminological/tidy-info-stats documentation built on Nov. 19, 2022, 11:23 p.m.
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View source: R/tidyBinaryInfoStats.R
| calculateBinaryMI | R Documentation |
Calculates multiple 2 class mutual information scores from confusion matrix probabilities in dplyr friendly manner
Description
The purpose of this is to make it possible to calculate MI in a DBPLYR sql table
Usage
calculateBinaryMI(df)
Arguments
df |
a dataframe containing one observation per row & full confusion matrix and marginal probabilities: i.e. p_x1, p_x0, p_y1, p_y0, p_x1y1, p_x0y1, p_x1y0, and p_x0y0 columns (see probabilitiesFromCounts) |
Value
the datatable with additional columns for entropy, mutual information, pointwise mutual information and normalised pointwise mutual information for all various combinations of outcome
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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