PDtoolkit (version 1.2.0)

predict.cdt: Predict method for custom decision tree

Description

Predict method for custom decision tree

Usage

# S3 method for cdt
predict(object, newdata = NULL, ...)

Value

Returns average default rate per leaf.

Arguments

object

Custom decision tree model (class cdt).

newdata

Optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted predictors are used.

...

further arguments passed to or from other methods.

Examples

#S3 method for class "cdt"
suppressMessages(library(PDtoolkit))
data(loans)
tree.res <- decision.tree(db = loans,
	rf = c("Account Balance", "Duration of Credit (month)"), 
	target = "Creditability",
	min.pct.obs = 0.05,
	min.avg.rate = 0.01,
	p.value = 0.05,
	max.depth = NA,
	monotonicity = TRUE)
str(tree.res)
#predict method - development sample
pred.1 <- predict(object = tree.res, newdata = NULL)
head(pred.1)
auc.model(predictions = pred.1$average, observed = loans$Creditability)
#predict method - new data
set.seed(321)
loans.m <- loans[sample(1:nrow(loans), 500, replace = TRUE), ]
pred.2 <- predict(object = tree.res, newdata = loans.m)
head(pred.2)
auc.model(predictions = pred.2$average, observed = loans.m$Creditability)