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Artificial Intelligence for Big Data

You're reading from  Artificial Intelligence for Big Data

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788472173
Pages 384 pages
Edition 1st Edition
Languages
Authors (2):
Anand Deshpande Anand Deshpande
Profile icon Anand Deshpande
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (19) Chapters close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. Big Data and Artificial Intelligence Systems 2. Ontology for Big Data 3. Learning from Big Data 4. Neural Network for Big Data 5. Deep Big Data Analytics 6. Natural Language Processing 7. Fuzzy Systems 8. Genetic Programming 9. Swarm Intelligence 10. Reinforcement Learning 11. Cyber Security 12. Cognitive Computing 1. Other Books You May Enjoy Index

Regression analysis


Regression analysis is a statistical modeling technique that is used for predicting or forecasting the occurrence of an event or the value of a continuous variable (dependent variable), based on the value of one or many independent variables. For example, when we want to drive from one place to another, there are numerous factors that affect the amount of time it will take to reach the destination, for example, the start time, distance, real-time traffic conditions, construction activities on the road, and weather conditions. All these factors impact the actual time it will take to reach the destination. As you can imagine, some factors have more impact than the others on the value of the dependent variable. In regression analysis, we mathematically sort out which variables impact the outcome, leading us to understand which factors matter most, which ones do not impact the outcome in a meaningful way, how these factors relate to each other, and mathematically, the quantified...

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