Title :
An E-SMOTE technique for feature selection in High-Dimensional Imbalanced Dataset
Author :
Deepa, T. ; Punithavalli, M.
Author_Institution :
Comput. Sci., Karpagam Univ., Coimbatore, India
Abstract :
Feature Selection in High-Dimensional Imbalanced Dataset (where one class outnumbers the other class) plays an imperative task in field of Data mining and Bio-informatics. This paper proposes a new technique called E-SMOTE Technique for balancing the dataset and SVM classification for selecting the features. It is evaluated using micro array dataset.
Keywords :
bioinformatics; data mining; pattern classification; support vector machines; E-SMOTE technique; SVM classification; bio-informatics; data mining; dataset balancing; feature selection; high-dimensional imbalanced dataset; micro array dataset; Bioinformatics; Cancer; Data mining; Feature extraction; Genetic algorithms; Machine learning; Support vector machines; E-SMOTE; Featue Selection; Imbalanced dataset; Support Vector Machine[SVM];
Conference_Titel :
Electronics Computer Technology (ICECT), 2011 3rd International Conference on
Conference_Location :
Kanyakumari
Print_ISBN :
978-1-4244-8678-6
Electronic_ISBN :
978-1-4244-8679-3
DOI :
10.1109/ICECTECH.2011.5941710
