install.packages('smbinning')
install.packages('InformationValue')
install.packages('klaR')
install.packages('party')
library(smbinning)
str(chileancredit)
# 看列联表
table(chileancredit$fgood)
table(chileancredit$cbinq)
table(chileancredit$cbterm)
table(chileancredit$cblineut)
data1=chileancredit
table(data1$fgood,data1$cbinq)
table(data1$home)
x=str(data1)[1]
# 获得dataframe的变量列表
is.factor(data1$fgood)
for (x in names(data1)) {
if (is.factor(x)=TRUE) {
print(x)
}
}
x=names(data1)
data1.x[2]
head(data1)
str(data1)
is.factor(data1$cbinq)
if (is.factor(data1$cbinq)==TRUE) {
print(1)
}
is.factor(data1[,5])
is.integer(data1[,2])
is.numeric(data1[,1])
mode(data1)
length(mode(data1))
desribe()
summary(data1$fgood)[1]
attributes(data1$fgood)
levels(data1$cbinq)
# 找不是factor类型的变量
numvar=list()
append(numvar,x[1],after=length(x))
numvar[1][1]
for (i in 1:length(x)) {
if (is.factor(data1[,i])==FALSE) {
print(x[i])
}
}
y=[]
x[2]
names(data1)
length(x)
length(str(data1))
#
nrow(complete.cases(chileancredit$fgood))
prop.table(chileancredit$fgood)
tapply(chileancredit$fgood)
# 对连续smbinning的测试
res=smbinning(df=data1,y='fgood',x='cbs1',p=0.05)
res$ivtable
data2=na.omit(data1)
nrow(data2)
install.packages('InformationValue')
install.packages('klaR')
install.packages('party')
library(smbinning)
str(chileancredit)
# 看列联表
table(chileancredit$fgood)
table(chileancredit$cbinq)
table(chileancredit$cbterm)
table(chileancredit$cblineut)
data1=chileancredit
table(data1$fgood,data1$cbinq)
table(data1$home)
x=str(data1)[1]
# 获得dataframe的变量列表
is.factor(data1$fgood)
for (x in names(data1)) {
if (is.factor(x)=TRUE) {
print(x)
}
}
x=names(data1)
data1.x[2]
head(data1)
str(data1)
is.factor(data1$cbinq)
if (is.factor(data1$cbinq)==TRUE) {
print(1)
}
is.factor(data1[,5])
is.integer(data1[,2])
is.numeric(data1[,1])
mode(data1)
length(mode(data1))
desribe()
summary(data1$fgood)[1]
attributes(data1$fgood)
levels(data1$cbinq)
# 找不是factor类型的变量
numvar=list()
append(numvar,x[1],after=length(x))
numvar[1][1]
for (i in 1:length(x)) {
if (is.factor(data1[,i])==FALSE) {
print(x[i])
}
}
y=[]
x[2]
names(data1)
length(x)
length(str(data1))
#
nrow(complete.cases(chileancredit$fgood))
prop.table(chileancredit$fgood)
tapply(chileancredit$fgood)
# 对连续smbinning的测试
res=smbinning(df=data1,y='fgood',x='cbs1',p=0.05)
res$ivtable
data2=na.omit(data1)
nrow(data2)