train<-data.frame(ClaimID=c(1,2,3), RearEnd = c(TRUE, FALSE, TRUE), Fraud = c(TRUE, FALSE, TRUE))
train
## ClaimID RearEnd Fraud
## 1 1 TRUE TRUE
## 2 2 FALSE FALSE
## 3 3 TRUE TRUE
library(rpart)
## Warning: package 'rpart' was built under R version 4.3.3
mytree<- rpart(Fraud~RearEnd, data = train, method = "class")
mytree
## n= 3
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 3 1 TRUE (0.3333333 0.6666667) *
mytree<- rpart(Fraud~RearEnd,
data = train,
method = "class",
minsplit = 2,
minbucket = 1)
mytree
## n= 3
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 3 1 TRUE (0.3333333 0.6666667)
## 2) RearEnd< 0.5 1 0 FALSE (1.0000000 0.0000000) *
## 3) RearEnd>=0.5 2 0 TRUE (0.0000000 1.0000000) *
library(rattle)
## Warning: package 'rattle' was built under R version 4.3.3
## Loading required package: tibble
## Warning: package 'tibble' was built under R version 4.3.2
## Loading required package: bitops
## Rattle: A free graphical interface for data science with R.
## Version 5.5.1 Copyright (c) 2006-2021 Togaware Pty Ltd.
## Type 'rattle()' to shake, rattle, and roll your data.
library(rpart.plot)
## Warning: package 'rpart.plot' was built under R version 4.3.3
library(RColorBrewer)
fancyRpartPlot(mytree, caption = NULL)
mytree<- rpart(Fraud~RearEnd,
data = train,
method = "class",
parms = list(split='information'),
minsplit = 2,
minbucket = 1)
mytree
## n= 3
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 3 1 TRUE (0.3333333 0.6666667)
## 2) RearEnd< 0.5 1 0 FALSE (1.0000000 0.0000000) *
## 3) RearEnd>=0.5 2 0 TRUE (0.0000000 1.0000000) *
fancyRpartPlot(mytree, caption = NULL)
train<-data.frame(ClaimID=c(1,2,3), RearEnd = c(TRUE, FALSE, TRUE), Fraud = c(TRUE, FALSE, FALSE))
train
## ClaimID RearEnd Fraud
## 1 1 TRUE TRUE
## 2 2 FALSE FALSE
## 3 3 TRUE FALSE
library(rpart)
mytree<- rpart(Fraud~RearEnd, data = train, method = "class")
mytree
## n= 3
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 3 1 FALSE (0.6666667 0.3333333) *
mytree<- rpart(Fraud~RearEnd,
data = train,
method = "class",
minsplit = 2,
minbucket = 1,
cp=-1)
mytree
## n= 3
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 3 1 FALSE (0.6666667 0.3333333)
## 2) RearEnd< 0.5 1 0 FALSE (1.0000000 0.0000000) *
## 3) RearEnd>=0.5 2 1 FALSE (0.5000000 0.5000000) *
fancyRpartPlot(mytree, caption = NULL)
train<-data.frame(ClaimID=c(1:7),
RearEnd = c(TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE),
Whiplash = c(TRUE,TRUE, TRUE, TRUE, TRUE, FALSE, FALSE),
Fraud = c(TRUE,TRUE,TRUE,FALSE, FALSE, FALSE, FALSE))
train
## ClaimID RearEnd Whiplash Fraud
## 1 1 TRUE TRUE TRUE
## 2 2 TRUE TRUE TRUE
## 3 3 FALSE TRUE TRUE
## 4 4 FALSE TRUE FALSE
## 5 5 FALSE TRUE FALSE
## 6 6 FALSE FALSE FALSE
## 7 7 FALSE FALSE FALSE
mytree<- rpart(Fraud~RearEnd,
data = train,
method = "class",
parms = list(split='information'),
minsplit = 2,
minbucket = 1)
mytree
## n= 7
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 7 3 FALSE (0.5714286 0.4285714)
## 2) RearEnd< 0.5 5 1 FALSE (0.8000000 0.2000000) *
## 3) RearEnd>=0.5 2 0 TRUE (0.0000000 1.0000000) *
fancyRpartPlot(mytree, caption = NULL)
lossmatrix<- matrix(c(0,1,2,0), byrow = TRUE, nrow = 2)
lossmatrix
## [,1] [,2]
## [1,] 0 1
## [2,] 2 0
mytree<- rpart(Fraud~RearEnd + Whiplash,
data = train,
method = "class",
maxdepth = 1,
minsplit = 2,
minbucket = 1,
parms = list(loss = lossmatrix))
mytree
## n= 7
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 7 4 TRUE (0.5714286 0.4285714)
## 2) RearEnd< 0.5 5 2 FALSE (0.8000000 0.2000000) *
## 3) RearEnd>=0.5 2 0 TRUE (0.0000000 1.0000000) *
fancyRpartPlot(mytree, caption = NULL)
train<-data.frame(ClaimID=c(1,2,3,4,5),
Activity = factor( x = c("active", "very active", "very active", "inactive", "very inactive"),
levels = c("very inactive", "inactive", "active", "very active")),
Fraud = c(FALSE, TRUE, TRUE, FALSE, TRUE))
train
## ClaimID Activity Fraud
## 1 1 active FALSE
## 2 2 very active TRUE
## 3 3 very active TRUE
## 4 4 inactive FALSE
## 5 5 very inactive TRUE
mytree<- rpart(Fraud~Activity,
data = train,
method = "class",
minsplit = 2,
minbucket = 1)
fancyRpartPlot(mytree, caption = NULL)
train<-data.frame(ClaimID=c(1,2,3,4,5),
Activity = factor( x = c("active", "very active", "very active", "inactive", "very inactive"),
levels = c("very inactive", "inactive", "active", "very active"), order = TRUE),
Fraud = c(FALSE, TRUE, TRUE, FALSE, TRUE))
train
## ClaimID Activity Fraud
## 1 1 active FALSE
## 2 2 very active TRUE
## 3 3 very active TRUE
## 4 4 inactive FALSE
## 5 5 very inactive TRUE
mytree<- rpart(Fraud~Activity,
data = train,
method = "class",
minsplit = 2,
minbucket = 1)
fancyRpartPlot(mytree, caption = NULL)
train<-data.frame(ClaimID=c(1:10),
RearEnd = c(TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE),
Whiplash = c(TRUE,TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE),
Activity = factor( x = c("active", "very active", "very active",
"inactive", "very inactive", "inactive", "very inactive", "inactive",
"active" , "very active"), levels = c("very inactive", "inactive", "active", "very active"),
ordered = TRUE),
Fraud = c(FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, TRUE))
train
## ClaimID RearEnd Whiplash Activity Fraud
## 1 1 TRUE TRUE active FALSE
## 2 2 TRUE TRUE very active TRUE
## 3 3 TRUE TRUE very active TRUE
## 4 4 FALSE TRUE inactive FALSE
## 5 5 FALSE TRUE very inactive FALSE
## 6 6 FALSE FALSE inactive TRUE
## 7 7 FALSE FALSE very inactive TRUE
## 8 8 TRUE FALSE inactive FALSE
## 9 9 TRUE FALSE active FALSE
## 10 10 FALSE TRUE very active TRUE
mytree<- rpart(Fraud~RearEnd + Whiplash + Activity,
data = train,
method = "class",
minsplit = 2,
minbucket = 1,
cp=-1)
fancyRpartPlot(mytree, caption = NULL)
names(mytree)
## [1] "frame" "where" "call"
## [4] "terms" "cptable" "method"
## [7] "parms" "control" "functions"
## [10] "numresp" "splits" "csplit"
## [13] "variable.importance" "y" "ordered"
mytree$variable.importance
## Activity Whiplash RearEnd
## 2.7142857 2.0000000 0.8571429
print(mytree)
## n= 10
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 10 5 FALSE (0.5000000 0.5000000)
## 2) Activity=very inactive,inactive,active 7 2 FALSE (0.7142857 0.2857143)
## 4) RearEnd>=0.5 3 0 FALSE (1.0000000 0.0000000) *
## 5) RearEnd< 0.5 4 2 FALSE (0.5000000 0.5000000)
## 10) Whiplash>=0.5 2 0 FALSE (1.0000000 0.0000000) *
## 11) Whiplash< 0.5 2 0 TRUE (0.0000000 1.0000000) *
## 3) Activity=very active 3 0 TRUE (0.0000000 1.0000000) *
mytree<-prune(mytree, cp = 0.21)
fancyRpartPlot(mytree)
