Clustering in R language
$10-30 USD
Paid on delivery
Q2. 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.
Q4. Implement Naïve Bayes using ‘Hair Eye Colour’ dataset in R
data("HairEyeColor")
Q1. Implement Naïve Bayes (Hint: use e1071)
Q2. Show the Naïve Bayes by using visualization.
Q3. Predict and Create Confusion Matrix.
Q4. Find Accuracy, Precision, Recall based on Confusion matrix.
Project ID: #13694213
About the project
7 freelancers are bidding on average $71 for this job
Hi I am a very experienced statistician and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have d More