December 2016
Beginner to intermediate
392 pages
8h 13m
English
Content preview from Apache Spark for Data Science CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Missing value treatment
Missing data in the training dataset can reduce the fitness of a model or can lead to a biased model because we have not analyzed the behavior and relationship with other variables correctly. This could also lead to wrong predictions or classifications. The reasons for the occurrence of the missing values could be that while extracting data from multiple sources, there is a possible chance to have missing data. Hence, using some hashing procedure ensures that the data extraction is correct. The errors that occur at the time of data collection are tougher to correct as the values might miss at random and the missing values might also depend on the unobserved predictors.
Getting ready
To step through this recipe, you will need ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.