Protein Classification Using Hybrid Feature Selection Technique

被引:0
|
作者
Singh, Upendra [1 ]
Tripathi, Sudhakar [1 ]
机构
[1] Natl Inst Technol Patna, Dept Comp Sci & Engn, Patna, Bihar, India
关键词
Classification Machine leaning; Data mining; Feature selection; Function prediction; PREDICTION;
D O I
10.1007/978-981-10-3433-6_97
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Protein function prediction is a challenging classification problem. A computational method is vital to perform the function prediction of Proteins. For this various Feature Selection techniques had proposed by eminent researcher. But several techniques are model based or for a specific type of problem. In this paper, we make a comparative analysis of different supervised machine learning methods for the prediction of functional classes of proteins using a set of physiochemical features. For an attribute or feature selection we have used a novel hybrid feature selection technique to overcome some of the limitations of existing technique and also present a comparative analysis of the classification of enzymes function or family using different computational intelligence techniques with proposed hybrid feature selection.
引用
收藏
页码:813 / 821
页数:9
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