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
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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

OpenCitations Citation Count
307
Source
Methods in Molecular Biology
Volume
1107
Issue
Start Page
105
End Page
128
PlumX Metrics
Citations
CrossRef : 255
Scopus : 407
PubMed : 116
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Mendeley Readers : 3574
SCOPUS™ Citations
406
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Web of Science™ Citations
299
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Page Views
39049
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Downloads
36711
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