Multilabel Classification of Membrane Protein in Human by Decision Tree (DT) Approach
Nijil Raj N1 and T. Mahalekshmi2

1Department of Computer Science and Engineering Younus College of Engineering and Technology, Vadakkevila,Kollam-691010, India.

2Sree Narayan Institute of Technology Vadakkevila, Kollam-691010, India.

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Abstract: Multi-label  classification  methods  are  important  in  various  fields,such  as  protein  type,protein  function, semantic scene classification and music categorization . In multi-label classification, each sample can be associated with a set of class labels. In protein type classification, one of the major types of protein is membrane protein. The Membrane proteins are performing different cellular processes and important functions, which are based on the protein types. Each membrane protein have different rolls at the same time. In this study we proposes membrane protein  type  classification using  Decision Tree  (DT)  classification algorithm. The  DT  classifies a  membrane protein into six types . An essential set of features are extracted from the membrane protein dataset S1 which are used for the proposed method,and it was revealed an accuracy of 69.81%, whereas existing methods network based and shortest path revealed an accuracy of 66.78%,54.97%.The accuracy got in the existing methods are not for the full set of protein in dataset S1, but it is achieved after removal of few unannotated protein. Both accuracy wise and complexity wise, the proposed method seems to be better than the existing method

Keywords: Multi-Label Classification; DT; Membrane Type Classification

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