[GitHub] [ignite] avplatonov commented on a change in pull request #6567: IGNITE-9978 Implement Compound Naive Bayes classifier

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avplatonov commented on a change in pull request #6567: IGNITE-9978 Implement Compound Naive Bayes classifier
URL: https://github.com/apache/ignite/pull/6567#discussion_r290211457
 
 

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 File path: modules/ml/src/main/java/org/apache/ignite/ml/naivebayes/discrete/DiscreteNaiveBayesTrainer.java
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 @@ -49,6 +52,9 @@
     /** The threshold to convert a feature to a discrete value. */
     private double[][] bucketThresholds;
 
+    /** Feature ids which should be skipped. By defaut all features are processed. */
+    private Collection<Integer> featureIdsToSkip = emptyList();
+
     /** {@inheritDoc} */
     @Override public <K, V> DiscreteNaiveBayesModel fit(DatasetBuilder<K, V> datasetBuilder,
                                                         Preprocessor<K, V> extractor) {
 
 Review comment:
   @dehasi , How do you think, maybe we may remove featureIdsToSkip logic from trainers and models and in CompoundBayess we may create to Preprocessors that wrap input preprocessor by features filtering logic? In this case we avoid modification in Discrete and Gauss models and save this logic in one place.

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