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LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES: Cancer Data Classification - Softcover
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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About the Author:
I,Dr.R.Mallika,India obtained my PhD in Computer Science in 2010 .With teaching experience of 12 Yrs and currently associated with Tamilnadu College of Engineering,India as Director,Department of Master of Computer applications.With research experience of 5 years published more than 15 International publications in Conferences and Journals.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2011
- ISBN 10 3844316590
- ISBN 13 9783844316599
- BindingPaperback
- Number of pages104
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LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES: Cancer Data Classification
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Linear Data Mining Model with Very Few Minimum Gene Features
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LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES Cancer Data Classification
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Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 104 pp. Englisch. Seller Inventory # 9783844316599
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LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES : Cancer Data Classification
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Book Description Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783844316599
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LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES Cancer Data Classification
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LINEAR DATA MINING MODEL WITH VERY FEW MINIMUM GENE FEATURES
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Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mallika Dr.RI,Dr.R.Mallika,India obtained my PhD in Computer Science in 2010 .With teaching experience of 12 Yrs and currently associated with Tamilnadu College of Engineering,India as Director,Department of Master of Computer applic. Seller Inventory # 5472116
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