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Smarter Decisions - The Intersection of Internet of Things and Decision Science

You're reading from   Smarter Decisions - The Intersection of Internet of Things and Decision Science A comprehensive guide for solving IoT business problems using decision science

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781785884191
Length 392 pages
Edition 1st Edition
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Author (1):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
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Table of Contents (10) Chapters Close

Preface 1. IoT and Decision Science FREE CHAPTER 2. Studying the IoT Problem Universe and Designing a Use Case 3. The What and Why - Using Exploratory Decision Science for IoT 4. Experimenting Predictive Analytics for IoT 5. Enhancing Predictive Analytics with Machine Learning for IoT 6. Fast track Decision Science with IoT 7. Prescriptive Science and Decision Making 8. Disruptions in IoT 9. A Promising Future with IoT

Linear regression - predicting a continuous outcome

There are a variety of statistical techniques available that can be used for prediction. Their usage is defined by the type of the dependent variable (continuous/categorical). A different technique or algorithm is required to solve these two different categories. We can use linear regression to predict a continuous variable and logistic regression for a categorical variable. A plethora of other techniques are available for these cases, but let's start solving the problem of predicting a continuous variable using linear regression.

Prelude

Before we begin understanding what we are going to build, let's take a moment to clearly understand the requirements from John's team and also study about how they plan to use the results. The team needs our help in building a system that can predict the actual quality parameter (Output Quality Parameter 2) before the manufacturing process. The team of technicians and store managers plan...

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