Package org.apache.ignite.examples.ml.regression.logistic.bagged

Class BaggedLogisticRegressionSGDTrainerExample

  • public class BaggedLogisticRegressionSGDTrainerExample
extends java.lang.Object
    This example shows how bagging technique may be applied to arbitrary trainer. As an example (a bit synthetic) logistic regression is considered.

    Code in this example launches Ignite grid and fills the cache with test data points (based on the Iris dataset).

    After that it trains bootstrapped (or bagged) version of logistic regression trainer. Bootstrapping is done on both samples and features (Samples bagging, Features bagging).

    Finally, this example applies cross-validation to resulted model and prints accuracy if each fold.

    • Method Summary

      All Methods Static Methods Concrete Methods 
      Modifier and Type Method Description
      static void main​(java.lang.String[] args)
      Run example.

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • BaggedLogisticRegressionSGDTrainerExample

        public BaggedLogisticRegressionSGDTrainerExample()

    • Method Detail

      • main

        public static void main​(java.lang.String[] args)
                 throws java.io.IOException
        Run example.
        Throws:
        java.io.IOException