# R/IVCalc2.R In CollapseLevels: Collapses Levels, Computes Information Value and WoE

#### Documented in IVCalc2

```#' @title        IVCalc2
#'
#' @description  This function displays the Information Values of all the attributes in the data set
#'
#' @param dset   The data frame containing the data set
#'
#' @param resp   A character respresenting the  name of the binary outcome variable
#'               The binary outcome variable may be a factor with two levels or an integer (or numeric ) with two unique values
#'
#' @param bins   A number denoting the number of bins.Default value is 10
#'
#' @param adjFactor A number or a decimal denoting what is to be added to the number of responses (binary outcome variable is 1 ) or to the number of non responses (binary outcome variable is 0) if either is zero for any level of the attribute
#'
#'
#' @return       A data frame containing the Information Values for every attribute
#'
#' @examples
#'
#' # Load the German_Credit data set supplied with this package
#'
#' data("German_Credit")
#'
#' d<-data.frame()
#'
#' # Call the function as follows
#'
#'
#' # Information Value for all the attributes in the German_Credit data
#'
#' d
#'
#'
#' @export

{
dIV<-data.frame()
d<-data.frame()
d<-dset
if(class(dset[[resp]])=="factor")
{

d[[resp]]<-as.numeric(d[[resp]])
d[[resp]]<-ifelse(d[[resp]]==max(d[[resp]]),1,0)
}
if(class(dset[[resp]])=="numeric" | class(dset[[resp]])=="integer")
{
d[[resp]]<-ifelse(d[[resp]]==max(d[[resp]]),1,0)
}

for(i in 1:ncol(d))
{
if(names(d)[i]!= resp)
{
naml<-names(d)[i]
df<-data.frame()
df_tot<-data.frame()
df_one<-data.frame()
df_zero<-data.frame()

if(class(d[[i]])=="numeric" | class(d[[i]])=="integer")
{
nr<-length(dset[[i]])
n<-round(nr/bins)
n
GC1<-data.frame()
GC1<-d[order(d[[i]]),]
vec<-GC1[[i]]
br<-numeric(length = bins+1)
lrec<-length(vec)
for(k in 1:bins+1)
{
if(k==1)
{
br[k]<-vec[k]

}
else if (k==(bins+1))
{
br[k]<-vec[lrec]

}
else{
br[k]<-vec[((k-1)*n)+1]
}

}
br<-unique(br)
cbr<-cut(vec,breaks=br,right=FALSE,include.lowest = TRUE)

naml<-gsub(" ","",naml)
varnum<-paste('categorical',naml,sep="")
GC1<-cbind(GC1,cbr)
names(GC1)[ncol(GC1)]<-varnum
naml<-names(GC1)[ncol(GC1)]
d<-data.frame()
d<-GC1

}

df_tot <- d %>%  dplyr::group_by_(naml) %>% dplyr::summarise(tot=n())
df_tot<-as.data.frame(df_tot)

df_one <- d %>%  dplyr::filter(d[[resp]]==1) %>% dplyr::group_by_(naml) %>% dplyr::summarise(bad=n())

df_one<-as.data.frame(df_one)

one_rate <- (df_one[,2]/sum(df_one[,2]))*100

df_zero <- d %>%  dplyr::filter(d[[resp]]==0) %>% dplyr::group_by_(naml) %>% dplyr::summarise(good=n())

df_zero<-as.data.frame(df_zero)

zero_rate<-(df_zero[,2]/sum(df_zero[,2]))*100

if(nrow(df_tot)>nrow(df_zero))
{
zero<-as.numeric()
zero<-df_tot[,2]-df_one[,2]
zero_rate<-as.numeric()
zero_rate<-(zero/sum(zero))*100
df<-cbind(df_tot,response=df_one[,2],non_response=zero,response_pct=one_rate,non_response_pct=zero_rate)

}
else if(nrow(df_tot)>nrow(df_one))
{

one<-as.numeric()
one<-df_tot[,2]-df_zero[,2]
one_rate<-as.numeric()
one_rate<-(one/sum(one))*100
df<-cbind(df_tot,response=one,non_response=df_zero[,2],response_pct=one_rate,non_response_pct=zero_rate)

}
else
{
df<-cbind(df_tot,response=df_one[,2],non_response=df_zero[,2],response_pct=one_rate,non_response_pct=zero_rate)
}

dfiv<-data.frame()
dfiv<-df

dfiv\$response_pct<-(dfiv\$response/sum(dfiv\$response))
dfiv\$non_response_pct<-(dfiv\$non_response/sum(dfiv\$non_response))
woe<-numeric()
iv<-numeric()

woe<-log(dfiv\$non_response_pct/dfiv\$response_pct)

if(sum(dfiv\$response==0)>0)
{
woe[dfiv\$response==0]<-0
}
if(sum(dfiv\$non_response==0)>0)
{
woe[dfiv\$non_response==0]<-0
}

iv<-(dfiv\$non_response_pct-dfiv\$response_pct)*woe

dfiv<-cbind(dfiv,woe=woe,iv=iv)

IV<-sum(dfiv\$iv)

dfiv\$response_pct<-(dfiv\$response/sum(dfiv\$response))
dfiv\$non_response_pct<-(dfiv\$non_response/sum(dfiv\$non_response))

dIV<-rbind(dIV,data.frame(names(d)[i],sum(iv)))

}
}

names(dIV)<-c("Variable","IV")
return(dIV)
}
```

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CollapseLevels documentation built on Dec. 4, 2017, 5:05 p.m.