---
title: "rpart - pima indians"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r}
library(rpart)
library(rpart.plot)
set.seed(123)
```


The data on the Pima indians can be found in the `MASS` package

```{r}
data(Pima.tr, package = "MASS")
head(Pima.tr)
```

Fit the a `rpart` model by default settings
```{r}
pima_rp1 <- rpart(type ~ ., data = Pima.tr)
```

Look at the `cp` complexity parameter
```{r}
plotcp(pima_rp1)
```

## Looking for plateau effect

```{r}
set.seed(2018)
pima_rp2 <- rpart(type~.,data=Pima.tr,cp=0)
plotcp(pima_rp2)
pima_rp2_pruned <- prune(pima_rp2, cp = 0.11)
```

## Plot the trees

```{r}
par(mfrow=c(1,2))
rpart.plot(pima_rp1, main="Default settings",
           xcompact=FALSE, ycompact=FALSE, type=2, extra=1)

rpart.plot(pima_rp2_pruned, main="rpart.control(cp=0.11)",
           xcompact=FALSE, ycompact=FALSE, type=2, extra=1)
```