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You're reading from  Julia for Data Science

Product typeBook
Published inSep 2016
Reading LevelBeginner
PublisherPackt
ISBN-139781785289699
Edition1st Edition
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Anshul Joshi
Anshul Joshi
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Anshul Joshi

Anshul Joshi is a data scientist with experience in recommendation systems, predictive modeling, neural networks, and high performance computing. His research interests encompass deep learning, artificial intelligence, and computational physics. Most of the time, he can be caught exploring GitHub or trying anything new he can get his hands on. You can also follow his personal blog.
Read more about Anshul Joshi

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Computing deviations


StatsBase.jl provides various functions to compute deviations between two datasets. This can be calculated using other functions, but to facilitate and for ease of use, StatsBase provides these efficiently implemented functions:

  • Mean absolute deviation: For two datasets, a and b, it is calculated as meanad(x,y) which is a wrapper over mean(abs(x-y)).

  • Maximum absolute deviation: For two datasets, a and b, it is calculated as maxad(x,y), which is a wrapper over maximum(abs(x-y)).

  • Mean squared deviation: For two datasets, a and b, it is calculated as msd(x,y), which is a wrapper over mean(abs2(x-y)).

  • Root mean squared deviation: For two datasets, a and b, it is calculated as rmsd(a,b), which is a wrapper over sqrt(msd(a, b)).

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Julia for Data Science
Published in: Sep 2016Publisher: PacktISBN-13: 9781785289699

Author (1)

author image
Anshul Joshi

Anshul Joshi is a data scientist with experience in recommendation systems, predictive modeling, neural networks, and high performance computing. His research interests encompass deep learning, artificial intelligence, and computational physics. Most of the time, he can be caught exploring GitHub or trying anything new he can get his hands on. You can also follow his personal blog.
Read more about Anshul Joshi