This notebook trains a linear regression model with regular fraud data and oversampled fraud data and compares the accuracy of both models. Finally, it uses a Decision Tree model to discover the most important feature when trying to predict fraud for this dataset.
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This notebook trains a linear regression model with regular fraud data and oversampled fraud data and compares the accuracy of both models. Finally, it uses a Decision Tree model to discover the most important feature when trying to predict fraud for this dataset.
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silvanoross/Fraud_Oversampling_Predictions
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This notebook trains a linear regression model with regular fraud data and oversampled fraud data and compares the accuracy of both models. Finally, it uses a Decision Tree model to discover the most important feature when trying to predict fraud for this dataset.
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