https://github.com/grantgasser/fraud-detection-linear-classifier

Using SageMaker's linear classifier to detect fraud. Addressing class imbalance and setting target metrics for Precision and Recall
https://github.com/grantgasser/fraud-detection-linear-classifier

class-imbalance classification fraud-detection sagemaker

Last synced: about 1 month ago
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Using SageMaker's linear classifier to detect fraud. Addressing class imbalance and setting target metrics for Precision and Recall

• Host: GitHub
• URL: https://github.com/grantgasser/fraud-detection-linear-classifier
• Owner: grantgasser
• Created: 2019-07-03T00:01:25.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2019-07-03T04:55:15.000Z (almost 6 years ago)
• Last Synced: 2025-02-08T18:14:40.339Z (3 months ago)
• Topics: class-imbalance, classification, fraud-detection, sagemaker
• Language: Jupyter Notebook
• Size: 91.8 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Linear Classifier for Fraud Detection

This project was done as part of the Udacity Machine Learning Engineer Nanodegree. See the Jupyter notebook for the interesting stuff.

# Summary

Using SageMaker's LinearLearner to detect credit card fraud. This exercise was about setting target metrics for Precision or Recall

as well as dealing with class imbalance.