data analysis clustering classification di sungheetha akey (6 risultati)

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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sungheetha AkeyThe academic work habits have evolved over the past eleven years on teaching and research. Significant contributions have been made based on the study that illustrates a unique pattern of data analysis. The study reave.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In MANET, EOPHMR approach has been used to conserve energy in the nodes. The energy reduction of the proposed EOPHMR approach is observed to be significant.A clustering algorithm that is a hybrid model of IG NRGA and KNN is presented for feature selection in microarray data sets. NRGA algorithm is used to do feature selection based on clustering technique. The approach uses ELM and FKNN as classifiers. The objective of the proposed systems is to get the highest accuracy when classifying the samples by the means a small subset of informative genes. A combination of two proposed gene selection techniques is used to solve the problem of the microarray high dimensionality. The combined technique gives high performance as it reduces the amount genes. It chooses gene for classification as each of them are much efficient binary classification techniques and typically give good results by attenuating their variety of attributes. 268 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In MANET, EOPHMR approach has been used to conserve energy in the nodes. The energy reduction of the proposed EOPHMR approach is observed to be significant.A clustering algorithm that is a hybrid model of IG NRGA and KNN is presented for feature selection in microarray data sets. NRGA algorithm is used to do feature selection based on clustering technique. The approach uses ELM and FKNN as classifiers. The objective of the proposed systems is to get the highest accuracy when classifying the samples by the means a small subset of informative genes. A combination of two proposed gene selection techniques is used to solve the problem of the microarray high dimensionality. The combined technique gives high performance as it reduces the amount genes. It chooses gene for classification as each of them are much efficient binary classification techniques and typically give good results by attenuating their variety of attributes.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.