score: Score a Database based on a Predictive Model
In BCA: Business and Customer Analytics

Description Usage Arguments Details Value Author(s)

Provides either an integer vector that contains the "desirability" rank of a case in a data set, the fitted probability of a desired response, or the fitted probability adjusted for the true response rate based on the fitted values of a predictive model.

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rankScore(model, data, targLevel)
rawProbScore(model, data, targLevel)
adjProbScore(model, data, targLevel, trueResp)

`model`	A character string containing the name of the model to use to score the database.
`data`	A data frame of the database to be scored. All the predictor variables of the model need to be amoung the variables of the data frame.
`targLevel`	The "desired" level of the y variable factor as a character string.
`trueResp`	The true "desired" response rate for the overall population of interest.

Only binomial glm, binary rpart, and binary nnet models can be used as the basis of scoring a database.

An integer vector that indicates the rank order desirability (a value of 1 means most desirable) of the correponding case of the database being scored or a probability measure bounded between zero and one.

Dan Putler

BCA documentation built on May 2, 2019, 1:26 p.m.