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Apache Spark for Data Science Cookbook

You're reading from   Apache Spark for Data Science Cookbook Solve real-world analytical problems

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Product type Paperback
Published in Dec 2016
Publisher
ISBN-13 9781785880100
Length 392 pages
Edition 1st Edition
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Authors (2):
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Padma Priya Chitturi Padma Priya Chitturi
Author Profile Icon Padma Priya Chitturi
Padma Priya Chitturi
Nagamallikarjuna Inelu Nagamallikarjuna Inelu
Author Profile Icon Nagamallikarjuna Inelu
Nagamallikarjuna Inelu
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Table of Contents (11) Chapters Close

Preface 1. Big Data Analytics with Spark 2. Tricky Statistics with Spark FREE CHAPTER 3. Data Analysis with Spark 4. Clustering, Classification, and Regression 5. Working with Spark MLlib 6. NLP with Spark 7. Working with Sparkling Water - H2O 8. Data Visualization with Spark 9. Deep Learning on Spark 10. Working with SparkR

Applying regression analysis for sales data


Regression analysis is a type of predictive modeling technique which investigates the relationship between variables. This is widely used for forecasting, time series modeling and finding the effect of relationships between the variables. In this, we try to fit a curve/line for the data points such that the differences between the distances of data points from the curve or line is minimized. Linear regression is the mostly frequently used technique. In this technique, the dependent variable is continuous, independent variables can be continuous or discrete, and the nature of the regression line is linear. The equation which is used to predict the value of the target variable is based on the following predictor variables:

y = aX +E 
y = target variable 
X = input variable 
a = regression coefficient 
E = the error term 

Regression techniques are driven by three metrics-the number of independent variables, the type of dependent...

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