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Machine Learning with Spark - Second Edition
book

Machine Learning with Spark - Second Edition

by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
April 2017
Intermediate to advanced
532 pages
12h 39m
English
Packt Publishing
Content preview from Machine Learning with Spark - Second Edition

Removing stop words

Stop words refer to common words that occur many times across almost all documents in a corpus (and across most corpuses). Examples of typical English stop words include and, but, the, of, and so on. It is a standard practice in text feature extraction to exclude stop words from the extracted tokens.

When using tf-idf weighting, the weighting scheme actually takes care of this for us. As stop words have a very low idf score, they will tend to have very low tf-idf weightings and thus less importance. In some cases, for information retrieval and search tasks, it might be desirable to include stop words. However, it can still be beneficial to exclude stop words during feature extraction, as it reduces the dimensionality of ...

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Publisher Resources

ISBN: 9781785889936