Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations

Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations

Okun, Oleg

Hardcover

Medical ReferenceChemistryGeneral Science

ISBN10: 1609605578
ISBN13: 9781609605575
Publisher: Idea Group Reference
Published: May 31 2011
Pages: 460
Weight: 2.20
Height: 1.30 Width: 7.20 Depth: 10.00
Language: English
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.

Also in

Chemistry

View All