April 2016
Beginner to intermediate
384 pages
8h 36m
English
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Chapter 6. Regression Methods
In this chapter, we will cover various techniques to predict the output of a power plant. You will learn the following recipes:
- Identifying and tackling multicollinearity in your data
- Building a linear regression model to predict the power plant output
- Using OLS to forecast how much electricity can be produced
- Estimating the output of an electric plant using CART
- Employing the kNN model in a regression problem
- Applying the Random Forest model to a regression analysis
- Gauging the amount of electricity a plant can produce using SVMs
- Training a Neural Network to predict the output of a power plant
Introduction
One of the most common problems in the real world is to predict certain quantities or, in more general terms, find a relationship ...
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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.