Introduction To Machine Learning

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Date

2014

Authors

Baştanlar, Yalın
Özuysal, Mustafa

Journal Title

Journal ISSN

Volume Title

Publisher

Humana Press

Open Access Color

Green Open Access

Yes

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Publicly Funded

No
Impulse
Top 10%
Influence
Top 1%
Popularity
Top 0.1%

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Abstract

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

Description

Keywords

Machine learning, Dimensionality reduction, Classification, Clustering, Performance metrics, Regression, Support Vector Machine, Discriminant Analysis, Bayes Theorem, Classification, Dimensionality reduction, Clustering, Regression, Performance metrics, Artificial Intelligence, Machine learning, Probability

Fields of Science

0301 basic medicine, 0303 health sciences, 03 medical and health sciences

Citation

Baştanlar, Y., and Özuysal, M. (2014). Introduction to machine learning. Methods in Molecular Biology, 1107, 105-128. doi:10.1007/978-1-62703-748-8_7

WoS Q

N/A

Scopus Q

Q4
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OpenCitations Citation Count
307

Source

Methods in Molecular Biology

Volume

1107

Issue

Start Page

105

End Page

128
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CrossRef : 255

Scopus : 407

PubMed : 116

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406

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299

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Page Views

39049

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Downloads

36711

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