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Apache Mahout Essentials

You're reading from   Apache Mahout Essentials Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781783554997
Length 164 pages
Edition 1st Edition
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Author (1):
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Jayani Withanawasam Jayani Withanawasam
Author Profile Icon Jayani Withanawasam
Jayani Withanawasam
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When is it appropriate to use Apache Mahout?

You should consider the following aspects before making a decision to use Apache Mahout as your machine learning library:

  • Are you looking for a machine learning algorithm for industry use with performance as a critical evaluation factor?
  • Are you looking for a free and open source solution?
  • Is your dataset large and growing at an alarming rate? (MATLAB, Weka, Octave, and R can be used to process KBs and MBs of data, but if your data volume is growing up to the GB level, then it is better to use Mahout.)
  • Do you want batch data processing as opposed to real-time data processing?
  • Are you looking for a mature library, which has been there in the market for a few years?

If all or most of the preceding considerations are met, then Mahout is the right solution for you.

You have been reading a chapter from
Apache Mahout Essentials
Published in: Jun 2015
Publisher:
ISBN-13: 9781783554997
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