Hybrid Learning Scheme for Data Mining Applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

• Type: Conference
• Year: 2004
• Where: HIS
• Authors: T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agrawal
• Keywords: Data Mining, Frequent Item Generation, HIS 2004, HIS 2007, Hybrid Learning Approach