TEJU: Fraud Detection and Improving Classification Performance for Bankruptcy Datasets Using Machine Learning Techniques
9 Pages Posted: 14 Jun 2019
Date Written: February 24, 2019
Fraud detection is one the major challenge problem. In this paper addressing of problem is fraud detection and improving performance. The fraudulent are changing day by day and it became very difficult to identify which data fraud and which is legitimate. In this paper addressing design a framework TEJU as fraud detection and improving classification performance for bankruptcy datasets using machine learning techniques. So we can reduce the problem by using machine learning techniques of kNN and main objective apply distance between two patterns compute similarity with classified into each class wise. Then experimental results based on framework to improve performance analysis of accuracies, ROC curve values and error rate.
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