Clustering in R language

Completed Posted 6 years ago Paid on delivery
Completed 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.

Data Mining R Programming Language

Project ID: #13694213

About the project

7 proposals Remote project Active 6 years ago

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mirevich

Hello, I can do any kind of work with data for you. My experience cover differ area of work: mining data, tidying, fit any analysis and so on. I can get data from SQL or any other source and visualize it in differen More

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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

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