Package org.apache.ignite.examples.ml.inference.exchange

Class KMeansClusterizationExportImportExample

  • public class KMeansClusterizationExportImportExample
extends java.lang.Object
    Run KMeans clustering algorithm (KMeansTrainer) over distributed dataset.

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

    After that it trains the model based on the specified data using KMeans algorithm.

    Finally, this example loops over the test set of data points, applies the trained model to predict what cluster does this point belong to, 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.

    • 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

      • KMeansClusterizationExportImportExample

        public KMeansClusterizationExportImportExample()

    • Method Detail

      • main

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