[jira] [Created] (SPARK-5273) Improve documentation examples for LinearRegression

["Dev Lakhani (JIRA)" <ji...@apache.org>]

Dev Lakhani created SPARK-5273:
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             Summary: Improve documentation examples for LinearRegression 
                 Key: SPARK-5273
                 URL: https://issues.apache.org/jira/browse/SPARK-5273
             Project: Spark
          Issue Type: Improvement
          Components: Documentation
            Reporter: Dev Lakhani
            Priority: Minor


In the document:
https://spark.apache.org/docs/1.1.1/mllib-linear-methods.html

Under
Linear least squares, Lasso, and ridge regression

The suggested method to use LinearRegressionWithSGD.train()
// Building the model
val numIterations = 100
val model = LinearRegressionWithSGD.train(parsedData, numIterations)

is not ideal even for simple examples such as y=x. This should be replaced with more real world parameters with step size:

val lr = new LinearRegressionWithSGD()
lr.optimizer.setStepSize(0.00000001)
lr.optimizer.setNumIterations(100)

or

LinearRegressionWithSGD.train(input,100,0.00000001)

To create a reasonable MSE. It took me a while using the dev forum to learn that the step size should be really small. Might help save someone the same effort when learning mllib.





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