World Scientific Publishing Company
Ensemble Learning : Pattern Classification Using Ensemble Methods
$125.22
Medical Information Science Reference
Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations
Product Code:
9781609605575
ISBN13:
9781609605575
Condition:
New
$272.11
Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations
$272.11
Machine learning is the branch of artificial intelligence whose goal is to develop algorithms that add learning capabilities to computers. Ensembles are an integral part of machine learning. A typical ensemble includes several algorithms performing the task of prediction of the class label or the degree of class membership for a given input presented as a set of measurable characteristics, often called features. Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification. This multidisciplinary text is at the intersection of computer science and biology and, as a result, can be used as a reference book by researchers and students from both fields. Each chapter describes the process of algorithm design from beginning to end and aims to inform readers of best practices for use in their own research.
| Author: Oleg Okun |
| Publisher: Medical Information Science Reference |
| Publication Date: May 31, 2011 |
| Number of Pages: 460 pages |
| Binding: Hardback or Cased Book |
| ISBN-10: 1609605578 |
| ISBN-13: 9781609605575 |
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