Kniha Knowledge Discovery using Machine Learning Algorithms Sujata Dash

Knowledge Discovery using Machine Learning Algorithms

Jazyk: Angličtina
Väzba: Brožovaná
Dostupnosť: Skladom u dodávateľa
Odosielame za 5-8 dní
56.06
The goal of this book is to provide a more effective way to extract features with highly important i...

Informácie o knihe

Jazyk
Angličtina
Väzba
Kniha - Brožovaná
Vydalo
2016
Stránok
192
EAN
9783659926204
Enbook ID
15359210
Hmotnosť
304
Rozmery
150 x 220 x 12

Kompletný popis

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.

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