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Feature Selection Based on Bi-objective Differential Evolution
Sunanda Das,Chi-Chang Chang,Asit Kumar Das,Arka Ghosh 한국정보과학회 2017 Journal of Computing Science and Engineering Vol.11 No.4
Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.
Feature Selection Based on Bi-objective Differential Evolution
Das, Sunanda,Chang, Chi-Chang,Das, Asit Kumar,Ghosh, Arka Korean Institute of Information Scientists and Eng 2017 Journal of Computing Science and Engineering Vol.11 No.4
Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.
Optical Absorption Studies of GaSbN Grown by Using Liquid Phase Epitaxy
이진구,채연식,Aniruddha Mondal,김미라,Sunanda Dhar,Tushar Dhabal Das 한국물리학회 2010 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.56 No.4
Optical absorption measurements were performed on GaSbN semiconductors with nitrogen concentrations in the layers ranging from 0.9 to 1.7%. The surface morphology was examined by using an atomic force microscope. The X-ray diffraction measurements confirmed the nitrogen concentrations in the layers. The reduction of the band gap with increasing amount of nitrogen in the layers was confirmed by their optical band edge absorption in the Fourier-transform infrared spectroscopy measurements. The absorption spectrum of the GaSbN semiconductor with a nitrogen concentration of 1.7% was fitted using the band anticrossing model (BAC) model.