Soft Computing for Machine Learning and Bioinformatics : An integrated approach for problem solving

Haider Banka

ISBN 10: 3639264843 / ISBN 13: 9783639264845

Editore: VDM Verlag Dr. Müller, 2010

Riguardo questo articolo

nach der Bestellung gedruckt Neuware - Printed after ordering - Hybridization using different soft computing tools has been explored for efficient data mining, clust- ering, and classification. An evolutionary-rough feature selection algorithm has been developed for feature selection and classi- fication of gene expre- ssion patterns. Next A detailed clustering algorithm is developed by integrating the advantage of both rough and fuzzy set theories. The remaining three chapters are devoted for biclustering problem. The whole work of this book is divided into the follow- ing: i) Mining important features from high dimen- sional gene datasets; ii) Biclustering or local stru- cture determination in gene expression data using soft tools; iii) Collaborative clustering for global structure determination in large data; iv) Covering various machine learning and bioinformatics applica- tions using soft computing; and v) A special chapter is written for designing a new paradigm for optimi- zation. The book focuses on some applications of the newly developed soft computing based methodologies for machine learning, optimization,and bioinformatic Problems. The book covers how to design a hybrid system for real life problem solving.

Codice articolo 9783639264845

Dati bibliografici

• Titolo: Soft Computing for Machine Learning and Bioinformatics : An integrated approach for problem solving
• Editore: VDM Verlag Dr. Müller
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 3639264843
• ISBN 13: 9783639264845
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 22 L x 15 A x 1,2 P centimetri 22 centimetri di larghezza per 15 centimetri di altezza per 1,2 centimetri di profondità
• Peso: 314 grammi

Descrizione articolo

Riassunto

Hybridization using different soft computing tools has been explored for efficient data mining, clust- ering, and classification. An evolutionary-rough feature selection algorithm has been developed for feature selection and classi- fication of gene expre- ssion patterns. Next A detailed clustering algorithm is developed by integrating the advantage of both rough and fuzzy set theories. The remaining three chapters are devoted for biclustering problem. The whole work of this book is divided into the follow- ing: i) Mining important features from high dimen- sional gene datasets; ii) Biclustering or local stru- cture determination in gene expression data using soft tools; iii) Collaborative clustering for global structure determination in large data; iv) Covering various machine learning and bioinformatics applica- tions using soft computing; and v) A special chapter is written for designing a new paradigm for optimi- zation. The book focuses on some applications of the newly developed soft computing based methodologies for machine learning, optimization,and bioinformatic Problems. The book covers how to design a hybrid system for real life problem solving.

L'autore

Dr. Haider Banka is an Assistant Professor in the Department of Computer Science and Engineering, Indian School of Mines, Dhan- bad, India. He has more than 7 years of teaching and Research Experience and published more than 18 research articles. His main research interest includes Soft Computing, M/c Learning, and Optimization.