Abstract:
There have been severe experiments from academics and merchandisers concerning
models for Predicting bankruptcy. The paper propounds an extensive rethink of work done
during 5 years in the petition of intellectual strategy to accomplish bankruptcy prediction
problems. Several machine learning directions are being used in this paper for Predicting
bankruptcy. Some algorithms: AdaBoost, Decision tree, J48, Bagging, Random Forest are
used in this paper. By traditional models, machine learning models offer enhancing
bankruptcy prediction accuracy. Different types of models are tested using several
evaluation metrics. The five years Bagging accuracy range is 95% within 97% among
another model. Here we include k-fold cross-validation(k=10) to measure our accuracy.
Bagging accuracy is high in this paper. A confusion matrix is used to recount the perfection
of a classification model that gives true values for knowing.