文章基本信息

标题：Survey on Feature Subset Selection Algorithm in Brain Interaction Patterns
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作者：K.Vidhyadevia ; M.Beema Mehraj ; Dr.K.P.Kaliyamurthie 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：3
DOI：10.15680/ijircce.2015.0303041
出版社：S&S Publications
摘要：Functional magnetic resonance imaging (FMRI) patterns provides the prospective to study brainfunction in a non-invasive way. The FMRI data are time series of 3-dimensional volume images of the brain. The datais traditionally analyzed within a mass-univariate framework essentially relying on classical inferential statistics.Handling of feature selection and clustering is a complicated process in interaction patterns of brain datasets. Tounderstand the complex interaction patterns among brain regions system proposes a novel clustering technique. Systemmodels each subject as multivariate time series, where the single dimensions characterize the FMRI signal at differentanatomical regions. In this survey paper, compares various research parameters for detection of clusters ofobjects with similar interaction patterns classification and clustering techniques used in it. The study papers waseffective to understand the techniques and gives idea to propose select the key features in the preprocessed datasetbased on the threshold values and Dimension Ranking algorithm was used to select the best cluster for assuring bestresult.
关键词：Data mining; Clustering; Interaction K-means Algorithm; Feature Subset Selection; Dimension;Ranking; FMRI.