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You're reading from  Julia for Data Science

Product typeBook
Published inSep 2016
Reading LevelBeginner
PublisherPackt
ISBN-139781785289699
Edition1st Edition
Languages
Julia
Concepts
Data Science
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Author (1)
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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Understanding z-score

Z-score refers to the standard deviations the element is away from the mean.

It is given by the following formula:

Here X represents the value of the element, σ is the standard deviation, and μ is the population mean.

Interpreting z-scores

  • z-score<0: The element is less than the mean

  • z-score>0: The element is greater than the mean

  • z-score=0: The element is equal to the mean

  • z-score=0.5: The element is 0.5 SD greater than the mean

In Julia, it is implemented as follows:

julia> zscore(X,  μ, σ)

μ and σ are optional as they can be calculated by the function.

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Julia for Data Science
Published in: Sep 2016Publisher: PacktISBN-13: 9781785289699
© 2016 Packt Publishing Limited All Rights Reserved

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

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