AI4OPT - Lecture 7 worksheet - DE&M II - Using RMSE with Longley dataset

# Load packages
library(caret)

## Warning: package 'caret' was built under R version 4.1.3

## Loading required package: ggplot2

## Loading required package: lattice

# Load the dataset
data(longley)

# prepare resampling method

trainControl <- trainControl(method ="cv", number=5)
set.seed(7)
fit <- train(Employed~., data=longley, method="lm", metric = "RMSE", trControl = trainControl)

# display results
print(fit)

## Linear Regression 
## 
## 16 samples
##  6 predictor
## 
## No pre-processing
## Resampling: Cross-Validated (5 fold) 
## Summary of sample sizes: 13, 13, 13, 13, 12 
## Resampling results:
## 
##   RMSE       Rsquared   MAE      
##   0.4656199  0.9977268  0.4023421
## 
## Tuning parameter 'intercept' was held constant at a value of TRUE