Verwandte Artikel zu Knowledge Discovery using Machine Learning Algorithms
Inhaltsangabe
The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Reseña del editor
The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells.
Biografía del autor
Dr. Sujata Dash is currently working as an Associate Professor of Computer Science Department of North Orissa University, Baripada, Odisha, India. She has 25 years of teaching and 17 years of research experience. She has published more than 85 technical papers in international journals/proceedings of international conferences/edited book.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
- VerlagLAP LAMBERT Academic Publishing
- Erscheinungsdatum2016
- ISBN 10 3659926205
- ISBN 13 9783659926204
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten192
- Kontakt zum HerstellerNicht verfügbar
Neu kaufen
Diesen Artikel anzeigen
EUR 52,90
Gratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerSuchergebnisse für Knowledge Discovery using Machine Learning Algorithms
Foto des Verkäufers
Knowledge Discovery using Machine Learning Algorithms
Verlag:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659926205
ISBN 13: 9783659926204
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dash SujataDr. Sujata Dash is currently working as an Associate Professor of Computer Science Department of North Orissa University, Baripada, Odisha, India. She has 25 years of teaching and 17 years of research experience. She has p. Bestandsnummer des Verkäufers 159147775
Anzahl: Mehr als 20 verfügbar
Foto des Verkäufers
Knowledge Discovery using Machine Learning Algorithms
Verlag:
LAP LAMBERT Academic Publishing Okt 2016, 2016
ISBN 10: 3659926205
ISBN 13: 9783659926204
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells.Books on Demand GmbH, Überseering 33, 22297 Hamburg 192 pp. Englisch. Bestandsnummer des Verkäufers 9783659926204
Anzahl: 2 verfügbar
Foto des Verkäufers
Knowledge Discovery using Machine Learning Algorithms
Verlag:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659926205
ISBN 13: 9783659926204
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells. Bestandsnummer des Verkäufers 9783659926204
Anzahl: 1 verfügbar
Foto des Verkäufers
Knowledge Discovery using Machine Learning Algorithms
Verlag:
LAP LAMBERT Academic Publishing Okt 2016, 2016
ISBN 10: 3659926205
ISBN 13: 9783659926204
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells. 192 pp. Englisch. Bestandsnummer des Verkäufers 9783659926204
Anzahl: 2 verfügbar
Beispielbild für diese ISBN
Knowledge Discovery using Machine Learning Algorithms
Verlag:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659926205
ISBN 13: 9783659926204
Neu
Paperback
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: Brand New. 192 pages. 8.66x5.91x0.44 inches. In Stock. Bestandsnummer des Verkäufers 3659926205
Anzahl: 1 verfügbar