Hi, Igniters! Currently, we have in Ignite ML next Pipeline API in alpha version via PipelineMDL and Pipeline classes.
I'm going to finish Pipeline API for the next release 2.8 and need you help in brainstorming You could find an example in master here <https://github.com/apache/ignite/blob/master/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/Step_5_Scaling_with_Pipeline.java> The snippet is added here PipelineMdl<Integer, Object[]> mdl = new Pipeline<Integer, Object[], Object[]>() .addFeatureExtractor(featureExtractor) .addLabelExtractor(lbExtractor) .addPreprocessor(new EncoderTrainer<Integer, Object[]>() .withEncoderType(EncoderType.STRING_ENCODER) .withEncodedFeature(1) .withEncodedFeature(6)) .addPreprocessor(new ImputerTrainer<Integer, Object[]>()) .addPreprocessor(new MinMaxScalerTrainer<Integer, Object[]>()) .addPreprocessor(new NormalizationTrainer<Integer, Object[]>() .withP(1)) .addTrainer(new DecisionTreeClassificationTrainer(5, 0)) .fit(ignite, dataCache); If you have any experience with Pipeline APi in another ML framework as scikit-learn, Spark, .NET ML and etc, please have a look at this API and write any suggestion about possible features and use-cases Feel free to add any suggestions or comments. -- Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/