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Based on available data from bank and parameters to identify the variables that influence the most, predict the bankruptcy of the given financial model

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Case study to predict bankruptcy

Bankruptcy dataset is a dataset which contains the financial information and the bankruptcy status of the companies for specific years. Variable D is the Bankruptcy/Non Bankruptcy flag, where 1 stands for Bankruptcy while 0 stands for Non Bankrupt companies. Variables R1 to R24 contain financial information which will be used while building a logistic regression model.

Predicting Bankruptcy-Case Solutions

Using your choice of classifiers, use R to produce several models to predict whether or not a firm goes bankrupt, assessing model performance on a validation partition.

Solution: Use Logistic Regression method to come to your conclusion

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Based on available data from bank and parameters to identify the variables that influence the most, predict the bankruptcy of the given financial model

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