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Mastering Machine Learning with Spark 2.x

You're reading from   Mastering Machine Learning with Spark 2.x Harness the potential of machine learning, through spark

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781785283451
Length 340 pages
Edition 1st Edition
Languages
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Authors (3):
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Alex Tellez Alex Tellez
Author Profile Icon Alex Tellez
Alex Tellez
Michal Malohlava Michal Malohlava
Author Profile Icon Michal Malohlava
Michal Malohlava
Max Pumperla Max Pumperla
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Max Pumperla
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Toc

Feature extraction

At this stage, we have only a raw text representing reviews, which is not sufficient to run any machine learning algorithm. We need to transform the text into a numeric format, aka perform the so-called "feature extraction" (it is as it sounds; we are taking the input data and extracting features which we will use to train a model). The method generates some new features based on input feature(s). There are many methods regarding how the text can be transformed into numeric features. We can count the number of words, length of text, or number of punctuations. However, to represent text in a systematic way that would reflect a text structure, we need more elaborate methods.

Feature extraction method– bag-of-words model

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