Journal of Data Mining in Genomics & Proteomics

Kalpesh H Vandra

Publications

• Research Article
  Information Theory Based Feature Selection for Multi-Relational Naive Bayesian Classifier
  Author(s): Vimalkumar B Vaghela, Kalpesh H Vandra and Nilesh K ModiVimalkumar B Vaghela, Kalpesh H Vandra and Nilesh K Modi
  
   Today data’s are stored in relation structures. In usual approach to mine these data, we often use to join several relations to form a single relation using foreign key links, which is known as flatten. Flatten may cause troubles such as time consuming, data redundancy and statistical skew on data. Hence, the critical issues arise that how to mine data directly on numerous relations. The solution of the given issue is the approach called multi-relational data mining (MRDM). Other issues are irrelevant or redundant attributes in a relation may not make contribution to classification accuracy. Thus, feature selection is an essential data pre-processing step in multi-relational data mining. By filtering out irrelevant or redundant features from relations for data mining, we improve classification accuracy, achieve good time performance, and improve comprehensibility of the mo.. View More»
  DOI: 10.4172/2153-0602.1000155

  Abstract PDF