Modified Approach for Classifying Multi Dimensional Data Cube Through Association Rule Mining for Granting Loans in Bank
In this paper, modified Approach for classifying Multi dimensional data cube is constructed. It explores data cubes in large Multi Dimensional Schema. Numerical and Nominal attributes are categorized based on Principal Component Analysis. Semantic relationships are identified by applying Multidimensional scaling. Additionally, AR is integrated for finding the inserting measures. Many algorithms have been proposed for applying Multi dimensional schema. But still some difficulties to category wise the integrated rules. The proposed approach suggested a new idea for categorizing the rules by using bank loan detect. This method provides accurate prediction and consumes less time than existing method. Keywords Association Rules, Datacubes, Data Mining, Multidimensional Schema, Information Gain