}
@Test
public void ridgeRegressionBuilderTest (){
List<Instance<double[]>> trainingData = setUp();
RidgeLinearModel ridgeLinearModel = ridgeLinearModelBuilder.buildPredictiveModel(trainingData);
double pythonRMSE = Math.sqrt(212.32/trainingData.size());
double pythonEpsilon = pythonRMSE/25.0;
double mse = 0;
for (Instance<double[]> instance : trainingData) {
double [] x = instance.getAttributes();
logger.info("prediction " + ridgeLinearModel.predict(x) + ". label: " + instance.getLabel());
mse+= Math.pow(ridgeLinearModel.predict(x) - (Double)instance.getLabel(), 2);
logger.info("un-normalized mse " + mse);
}
mse/=trainingData.size();
double RMSE = Math.sqrt(mse);
logger.info("mse_per_test_instance " + mse);