Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
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Integration of data mining in database systems is an open topic of research. The DBMS's power of dealing with lots of data and maintaining data integrity adds to the motivation of integrating it with data mining. We propose a method to integrate decision tree classification to do the required pre-computations and store it in database objects for later use. These pre-computed values get updated with the introduction of new data or change in the existing data for classification. Decision tree classification can readily make use of these pre-computed values to build classification models. Our approach is based on the column database to use it effectively for feature oriented calculations. This comparatively improves performance if classification is deemed to be performed on a high dimensional data.