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.
Feature Selection and Ensemble Methods for Bioinformatics
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$554.00
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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.
This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have...
The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. Bioinformatics Methods: From Omics to Next Generation Sequencing describes the...
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