https://github.com/faizelkhan/Insurance-Claim-Using-Machine-Learning-

Predicting property and casualty insurance claims: A Machine Learning Approach
https://github.com/faizelkhan/Insurance-Claim-Using-Machine-Learning-

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Predicting property and casualty insurance claims: A Machine Learning Approach

• Host: GitHub
• URL: https://github.com/faizelkhan/Insurance-Claim-Using-Machine-Learning-
• Owner: faizelkhan
• Created: 2017-06-15T16:12:16.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-06-15T17:14:56.000Z (over 7 years ago)
• Last Synced: 2024-08-13T07:12:59.596Z (5 months ago)
• Language: R
• Size: 8.79 KB
• Stars: 5
• Watchers: 1
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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• jimsghstars - faizelkhan/Insurance-Claim-Using-Machine-Learning- - Predicting property and casualty insurance claims: A Machine Learning Approach (R)

README

        
# Insurance Claim Using Machine Learning

## Predicting property and casualty insurance claims: A Machine Learning Approach

### Abstract:

Property and Casualty insurance companies often encounter problems in predicting the likelihood of a policyholder causing a claim. 

Some territories have few claim experiences, resulting in very sparse data. In addition, some data are highly dimensional in terms

of the predictors of the likelihood of a claim. 

In this research, simulated sparse claims data are used to identify the most appropriate predictive model for determining the likelihood

of a policyholder causing a claim. Machine learning algorithms such as the logit model and the support vector machine will be used to 

predict whether the future policyholder will incur a claim.

### Presentation Link:

http://prezi.com/2smclr8un8vu/?utm_campaign=share&utm_medium=copy&rc=ex0share

## Data Analysis

### driver.R 

This is the main file of this project. The algorithm in this file requires some external R libraries, which are already mentioned in the

comments in these files. The algorithm also gives us a choice to run either _Support Vector Machine(SVM)_ or _Logistic Regression(LR)_ 

and this can be done by commenting SVM  or LR source file code, respectively.

### DataProcessing.R

This file is to process the generated data and split it into training and test data.

 

### DataGen.R

This file generates the data of specific number of observations and feature ratios. 

### svm_linear.R

The file runs the SVM classification on the training data and then test the classifier on the test data to check the accuracy of the

classifier for the unknown data.

### logit_reg.R

The file runs the LR classification on the training data and then test the classifier on the test data to check the accuracy of the

classifier for the unknown data.