public class LinearRegressionLSQRTrainerWithMinMaxScalerExample
extends java.lang.Object

Run linear regression model based on LSQR algorithm (LinearRegressionLSQRTrainer) over cached dataset that was created using a minmaxscaling preprocessor (MinMaxScalerTrainer, MinMaxScalerPreprocessor).

Code in this example launches Ignite grid, fills the cache with simple test data, and defines minmaxscaling trainer and preprocessor.

After that it trains the linear regression model based on the specified data that has been processed using minmaxscaling.

Finally, this example loops over the test set of data points, applies the trained model to predict predict the target value and compares prediction to expected outcome (ground truth).

You can change the test data used in this example and re-run it to explore this algorithm further.