Package org.apache.ignite.examples.ml.tutorial

Class Step_3_Categorial_with_One_Hot_Encoder

  • public class Step_3_Categorial_with_One_Hot_Encoder
extends java.lang.Object
    Let's add two categorial features "sex", "embarked" to predict more precisely than in Step_1_Read_and_Learn..

    To encode categorial features the EncoderTrainer of the One-hot type will be used.

    Code in this example launches Ignite grid and fills the cache with test data (based on Titanic passengers data).

    After that it defines preprocessors that extract features from an upstream data and encode string values (categories) to double values in specified range.

    Then, it trains the model based on the processed data using decision tree classification.

    Finally, this example uses Evaluator functionality to compute metrics from predictions.

    • 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

      • Step_3_Categorial_with_One_Hot_Encoder

        public Step_3_Categorial_with_One_Hot_Encoder()

    • Method Detail

      • main

        public static void main​(java.lang.String[] args)
        Run example.