WOETable: WOETable

In InformationValue: Performance Analysis and Companion Functions for Binary Classification Models

Description

Compute the WOETable that shows the Weights Of Evidence (WOE) for each group and respeective Information Values (IVs).

Usage

WOETable(X, Y, valueOfGood = 1)

Arguments

X	The categorical variable stored as factor for which WOE Table is to be computed.
Y	The actual 1/0 flags for the binary response variable. It can take values of either 1 or 0, where 1 represents the 'Good' or 'Events' while 0 represents 'Bad' or 'Non-Events'.
valueOfGood	The value in Y that is used to represent 'Good' or the occurence of the event of interest. Defaults to 1.

Details

For a given actual for a Binary Y variable and a categorical X variable stored as factor, the WOE table is generated with calculated WOE's and IV's

Value

The WOE table with the respective weights of evidence for each group and the IV's.

• CAT. The groups (levels) of the categorical X variable for which WOE is to be calculated.

• GOODS. The total number of "Goods" or "Events" in respective group.

• BADS. The total number of "Bads" or "Non-Events" in respective group.

• TOTAL. The total number of observations in respective group.

• PCT_G. The Percentage of 'Goods' or 'Events' accounted for by respective group.

• PCT_B. The Percentage of 'Bads' or 'Non-Events' accounted for by respective group.

• WOE. The computed weights of evidence(WOE) for respective group. The WOE values can be used in place of the actual group itself, thereby producing a 'continuous' alternative.

• IV. The information value contributed by each group in the X. The sum of IVs is the total information value of the categorical X variable.

Author(s)

Selva Prabhakaran [e-mail]

Examples

data('SimData')
WOETable(X=SimData$X.Cat, Y=SimData$Y.Binary)

Example output

     CAT GOODS  BADS TOTAL        PCT_G        PCT_B        WOE           IV
1 Group1   179  1500  1679 0.0246488571 0.0659108885 -0.9835731 0.0405842251
2 Group2   346   525   871 0.0476452768 0.0230688110  0.7253020 0.0178253591
3 Group3   560  1354  1914 0.0771137428 0.0594955620  0.2593798 0.0045698000
4 Group4     6     6     6 0.0008262187 0.0002636436  1.1422615 0.0006426079
5 Group5  4595 16369 20964 0.6327458001 0.7192635557 -0.1281591 0.0110880366
6 Group6   577   461  1038 0.0794546957 0.0202566131  1.3667057 0.0809063559
7 Group7   658  1670  2328 0.0906086478 0.0733807892  0.2108875 0.0036331398
8 Group8   327   859  1186 0.0450289177 0.0377449688  0.1764527 0.0012852725
9 Group9    14    14    14 0.0019278436 0.0006151683  1.1422615 0.0014994184

InformationValue documentation built on May 1, 2019, 9:12 p.m.