Kniha Knowledge Discovery using Machine Learning Algorithms Sujata Dash

Knowledge Discovery using Machine Learning Algorithms

Jazyk: Angličtina
Vazba: Brožovaná
Dostupnost: Skladem u dodavatele
Odesíláme za 5-8 dnů
1 278
The goal of this book is to provide a more effective way to extract features with highly important i...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2016
Stránek
192
EAN
9783659926204
Enbook ID
15359210
Hmotnost
304
Rozměry
150 x 220 x 12

Kompletní 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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