September 2017
Beginner to intermediate
412 pages
8h 55m
English
Content preview from Java Data AnalysisBecome 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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Summary
In this chapter, we have investigated several examples of regression analysis, including linear regression, polynomial regression, multiple linear regression, and more general curve fitting. In each case, the objective is to derive from a given dataset a function that can then be used to extrapolate from the given data to predict unknown values of the function.
We've seen that these regression algorithms work by solving a system of linear equations, called the normal equations, for the problem. That part of the solution can be done by various algorithms, such as Cramer's Rule, Gaussian Elimination, or LU decomposition.
We used several approaches to implement these algorithms, including Windows Excel, direct Java implementations, and the ...
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.