Implement Decision Tree in R

Implement Decision Tree in R. Create this dataset (Copy this below piece of code and paste it in your R) ---------------------------------------------------------------------------- data <- [login to view URL]( InsuranceID = c(1,2,3,4,5,6,7,8,9,10), Vehicle_Damage = c(TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE), Self_Injury = c(TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE), Claimer_Frequency = factor(c("active", "very active", "very active", "inactive", "very inactive" , "inactive", "very inactive", "active", "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)) ---------------------------------------------------------------------------------------- This data set is used by an Insurance Company to check whether the Claim is fraud or not. Insurance ID: The Claim ID. Vehicle Damage: Is the vehicle damage or not? Self-Injury: Is the person injured or not? Claimer Frequency: Frequency of the person claiming the Insurance. Fraud: If this is fraud or not? Q1. Implement Decision Trees (Hint: use Rpart) Q2. Find whether the fraud is done or not for Insurance ID 2 and 7? Q3. Show the Decision Trees by using visualization.