Classification Model for Credit Data

Data mining algorithms have become over the time more related to business and artificial intelligence. Data mining techniques are used for decision-making and prediction purpose. In this research paper, a model of three data mining algorithms is proposed. The model is tested on a credit dataset for different customers to determine if the credit tested is good (approved) or bad (denied). The three different algorithms used in this model are: Decision Tree (DT), K-Nearest Neighbors Algorithm (KNN), and Logistic Regression (LG). The accuracy, sensitivity and other performance measures of the models are also calculated.