NDLI: A new approach of microarray data dimension reduction for medical applications

Content Provider	IEEE Xplore Digital Library
Author	Katole, S.N. Karmore, S.P.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci. & Eng., G.H. Raisoni Coll. of Eng., Nagpur, India (Katole, S.N.; Karmore, S.P.)
Abstract	To employ and develop the performance of the dimensionality reduction for microarray data there is need of good dimension reduction technique. High-dimensional data bring great challenges in terms of computational complexity and classification performance. Therefore, it is necessary to effectively compress in a low-dimensional feature space from high dimensional feature space to design a learner with good performance. Feature extraction has a stronger ability to extract structure information in variables. Feature selection preserves the original features so that obtained feature subset has better explanatory ability. Therefore, dimension reduction is essential to study and understand the mechanism of practical problems of the microarray data. Dimension reduction is the important term which is majorly used in the big areas of genetics, medical and bioinformatics field. In medical applications for high dimensional cancer microarray data the dimension reduction is the important step. In this paper, a new Maximal Information-based Nonparametric Exploration method is proposed for the dimension reduction of the microarray data. In MINE method the MIC (Maximal Information Coefficient) plays the important role to show the relation between the data. The paper focused on improving the performance in terms of recognition accuracy, relevance, interpretability and redundancy, after comparing the performance of MINE method and Total PLS algorithm on data.
Starting Page	409
Ending Page	413
File Size	162463
Page Count	5
File Format	PDF
e-ISBN	9781479972258
DOI	10.1109/ECS.2015.7124936
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-02-26
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Relevancy Redundancy Classification algorithms Data mining Microwave integrated circuits Dimension reduction Accuracy Microarray data MINE Feature extraction Medical applications Recognition Cancer Principal component analysis
Content Type	Text
Resource Type	Article

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