Linear Regression Model

buildingModel.scala

//linear regression model
val lr = new LinearRegression().setLabelCol("medianHouseValue").setFeaturesCol("scaledFeatures")
      .setMaxIter(100)
      .setRegParam(0.3)
      .setElasticNetParam(0.8)
// Using Training set for model building
val lrModel = lr.fit(split(0))
    
// Print the coefficients and intercept for linear regression
println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
// Summarize the model over the training set and print out some metrics
val trainingSummary = lrModel.summary
println(s"numIterations: ${trainingSummary.totalIterations}")
println(s"objectiveHistory: [${trainingSummary.objectiveHistory.mkString(",")}]")
trainingSummary.residuals.show()
println(s"RMSE: ${trainingSummary.rootMeanSquaredError}")
println(s"r2: ${trainingSummary.r2}")