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You're reading from  Apache Mahout Essentials

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Published inJun 2015
Reading LevelIntermediate
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ISBN-139781783554997
Edition1st Edition
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Jayani Withanawasam
Jayani Withanawasam
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Jayani Withanawasam

Jayani Withanawasam is R&D engineer and a senior software engineer at Zaizi Asia, where she focuses on applying machine learning techniques to provide smart content management solutions. She is currently pursuing an MSc degree in artificial intelligence at the University of Moratuwa, Sri Lanka, and has completed her BE in software engineering (with first class honors) from the University of Westminster, UK. She has more than 6 years of industry experience, and she has worked in areas such as machine learning, natural language processing, and semantic web technologies during her tenure. She is passionate about working with semantic technologies and big data.
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Classification versus regression


Methods for prediction can be divided into two general groups, based on the outcome of the prediction algorithm, as follows:

  • When the data is discrete, we will refer to it as classification. Discriminant analysis and pattern recognition are the other similar terms used for classification.

  • When the data is continuous, we will refer to it as regression. Other terms used for regression are smoothing and curve estimation.

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Apache Mahout Essentials
Published in: Jun 2015Publisher: ISBN-13: 9781783554997

Author (1)

author image
Jayani Withanawasam

Jayani Withanawasam is R&D engineer and a senior software engineer at Zaizi Asia, where she focuses on applying machine learning techniques to provide smart content management solutions. She is currently pursuing an MSc degree in artificial intelligence at the University of Moratuwa, Sri Lanka, and has completed her BE in software engineering (with first class honors) from the University of Westminster, UK. She has more than 6 years of industry experience, and she has worked in areas such as machine learning, natural language processing, and semantic web technologies during her tenure. She is passionate about working with semantic technologies and big data.
Read more about Jayani Withanawasam