Dr.R Mallika

LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES

Cancer Data Classification

• Broschiertes Buch

Produktbeschreibung

Microarray classification has been a hot topic in recent years and attracted the attention of many researchers from different research fields such as data mining, machine learning and statistics. Gene expression data analysis plays a vital role in medical diagnosis and drug discovery.With huge volume of gene expression data,the possibilities of cancer classification have to be explored.Many methods have been proposed with promising results. Various statistical gene selection techniques, which are an integral pre-processing step for classification along with few supervised classification methods were used in various works.The initiation of efficient classification algorithm for cancer gene expression data has been exploded in health sector during recent years. Particular application of Data mining algorithms for microarray technologies is in cancer research with a goal of early diagnosis of cancer.In machine learning community,supervised learning is to build predictive models using gene expression measurements of a number of individuals with known class membership.This research work presents a new and novel supervised classification method for cancer classification and prediction.

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Produktdetails

• Verlag: LAP Lambert Academic Publishing
• Seitenzahl: 104
• Erscheinungstermin: 11. März 2011
• Englisch
• Abmessung: 220mm x 150mm x 7mm
• Gewicht: 173g
• ISBN-13: 9783844316599
• ISBN-10: 3844316590
• Artikelnr.: 33221673

Autorenporträt

I,Dr.R.Mallika,India obtained my PhD in Computer Science in 2010.With teaching experience of 12 Yrs and currently associated withTamilnadu College of Engineering,India as Director,Department ofMaster of Computer applications.With research experience of 5years published more than 15 International publications inConferences and Journals.