Prediction of bankruptcy is a phenomenon of increasing interest to firms who stand to lose money because on unpaid debts. Since computers can store huge dataset pertaining to bankruptcy making accurate predictions from them before hand is becoming important.
The main objective of this project is to use various classification algorithms on bankruptcy dataset to predict bankruptcies with satisfying accuracies long before the actual event.