woeregplot: Plot the charts for regresion models
In billyuanyao/WOECredit:

Description Usage Arguments Details Value Examples

Plot charts for each vairable in keeplist, including, relation chart, score chart, ROC curve chart

1	woeregplot(Data, keeplist = NULL, y, model)

`Data`	data frame with at least two columns
`keeplist`	Name of the Independent Variables keept for capping, if missing then for all Independent Variables
`y`	Name of the dependent Variables
`model`	Name of the model fitted by regression

Note: this is for credit modeling, and the most useful charts are relation chart, score chart and ROC curve Chart

test: data is from the Titanic project https://www.kaggle.com/c/titanic/data traindata <- read.csv('train.csv',header=T,na.strings=c("")) Data <- subset(traindata,select=c(2,3,5,6,7,8,10,12)) model<-woereg(Data=Data,keeplist=c('Fare','Pclass'),droplist=c('Sex','Embarked'),y='Survived') library(magrittr) library(ggplot2) library(ROCR) woeregplot(Data=Data,y='Survived',model=model)

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (Data, keeplist = NULL, y, model)
{
    if (is.null(keeplist)) {
        vallist <- coef(summary(model))[, 4]
        vallist <- vallist[!(names(vallist) %in% "(Intercept)")]
        keeplist <- c(names(vallist), y)
    }
    lscore <- predict(model, Data, type = "link")
    rscore <- predict(model, Data, type = "response")
    sdata <- data.frame(link = lscore, response = rscore, y = Data[,
        y], stringsAsFactors = FALSE)
    sdata %>% ggplot(aes(x = link, y = response, col = y)) +
        geom_point() + geom_rug() + ggtitle("link and response scores")
    rocp <- prediction(rscore, Data[, y])
    rocperf <- performance(rocp, "tpr", "fpr")
    plot(rocperf, colorize = TRUE)
  }