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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
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Authors (3):
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Alex Tellez Alex Tellez
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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

Data

In this chapter, we are going to use Physical Activity Monitoring Data Set (PAMAP2) published in the Machine Learning Repository by the University of Irvine: https://archive.ics.uci.edu/ml/datasets/PAMAP2+Physical+Activity+Monitoring

The full dataset contains 52 input features and 3,850,505 events describing 18 different physical activities (for example, walking, cycling, running, watching TV). The data was recorded by a heart rate monitor and three inertial measurement units located on the wrist, chest, and dominant side's ankle. Each event is annotated by an activity label describing the ground truth and also a timestamp. The dataset contains missing values indicated by the value NaN. Furthermore, some columns produced by sensors are marked as invalid ("orientation" - see dataset description):

Figure 1: Properties of dataset as published in the Machine Learning...
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