├── Final_project_BankruptcyPrediction.ipynb
├── README.md
└── bankruptcy
    ├── sample
        ├── 1st_yr.csv
        ├── 2nd_yr.csv
        ├── 3rd_yr.csv
        ├── 4th_yr.csv
        └── 5th_yr.csv
    └── train
        ├── 1st_yr.csv
        ├── 2nd_yr.csv
        ├── 3rd_yr.csv
        ├── 4th_yr.csv
        └── 5th_yr.csv


/README.md:
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1 | # Bankruptcy-Prediction-using-Machine-Learning
2 | *	Using various machine learning models (Gaussian Naïve Bayes, Logistic Regression, Support Vector Machine, Gradient Boosting Trees, Neural Networks) to predict whether a company will go bankrupt in the following years, based on 64 financial attributes of the company;
3 | *	Addressed the issue of imbalanced classes, different importance of each type of misclassification;
4 | *	Tune Parameters using Grid Search Cross Validation of best model GBM to achieve 0.96 accuracy, 0.62 recall and 0.77 f1 score;
5 | 


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