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Practical Predictive Analytics
book

Practical Predictive Analytics

by Ralph Winters
June 2017
Beginner to intermediate
576 pages
15h 22m
English
Packt Publishing
Content preview from Practical Predictive Analytics

Spark machine learning using logistic regression

Now that we have constructed our test and training datasets, we will begin by building a logistic regression model which will predict the outcome 1 or 0. As you will recall, 1 designates diabetes detected, while 0 designates diabetes not detected.

The syntax of a Spark glm is very similar to a normal glm. Specify the model using formula notation. Be sure to specify family = "binomial" to indicate that the outcome variable has only two outcomes:

# run glm model on Training dataset and assign it to object named "model"model <- spark.glm(outcome ~ pregnant + glucose + pressure + triceps + insulin + pedigree + age,family = "binomial", maxIter=100, data = df) summary(model)
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Publisher Resources

ISBN: 9781785886188Supplemental Content