IGNITE-9412: GDB convergence by error support #4670
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| @@ -95,7 +98,7 @@ public static void main(String... args) throws InterruptedException { | |||
| @NotNull private static CacheConfiguration<Integer, double[]> createCacheConfiguration() { | |||
| CacheConfiguration<Integer, double[]> trainingSetCfg = new CacheConfiguration<>(); | |||
| trainingSetCfg.setName("TRAINING_SET"); | |||
| trainingSetCfg.setAffinity(new RendezvousAffinityFunction(false, 10)); | |||
| trainingSetCfg.setAffinity(new RendezvousAffinityFunction(false, 1)); | |||
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It remained after debugging. I forget revert.
I will fix
| * | ||
| * @param factory Factory. | ||
| */ | ||
| public GDBLearningStrategy withCheckConvergenceStgyFactory(ConvergenceCheckStrategyFactory factory) { |
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I dislike the class which has in name and behaviour Strategy + Factory, is it required to use here?
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maybe I should use another name, but factory need to create checker on runtime (like sample size) and it need to avoid additional parameters (like DatasourceBuilder) for user api
I will rename CheckConvergenceStgy to ConvergenceChecker to avoid missunderstanding
| ModelsComposition mdl); | ||
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| /** | ||
| * Compute error on one element of dataset. |
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Maybe: Compute error for the specific vector?
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Yes it is
Thank you
| */ | ||
| public class FeatureMatrixWithLabelsOnHeapData implements AutoCloseable { | ||
| /** Matrix with features. */ | ||
| private final double[][] features; |
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I dislike this class which handles only double features. Maybe is better to use more widely used class like https://github.com/apache/ignite/blob/master/modules/ml/src/main/java/org/apache/ignite/ml/structures/LabeledVectorSet.java
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I understand you, but
I need to use such structure for DecisionTrees compaptibility in Gradient Boosting. If we implement Vector-structures support in DT later, then we can rewrite this part to your data structure
| * @param features Features. | ||
| * @param labels Labels. | ||
| */ | ||
| public FeatureMatrixWithLabelsOnHeapData(double[][] features, double[] labels) { |
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see #4670 (comment)
| /** Vector with labels. */ | ||
| private final double[] labels; | ||
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| public class DecisionTreeDataWithIndex extends FeatureMatrixWithLabelsOnHeapData implements AutoCloseable { |
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Will we have in database DTDataWihoutIndex? Should it be renamed?
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Yes, you're right
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| MeanAbsValueCheckConvergenceStgyFactory factory = new MeanAbsValueCheckConvergenceStgyFactory(0.1); | ||
| ModelsComposition notConvergedModel = new ModelsComposition(Collections.emptyList(), null) { | ||
| @Override public Double apply(Vector features) { |
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Could you please explain the meaning of the apply implentation here, in test
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I will move it to test-class fields
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| /** Mean error more sensitive to anomalies in data */ | ||
| @Test | ||
| public void testComputing2() { |
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Rename test to something meaningful (like the comment above)
| public class MedianOfMedianConvergenceCheckStrategyTest { | ||
| /** */ | ||
| @Test | ||
| public void testComputing() { |
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rename the test to the something meaningful
…-9412 # Conflicts: # examples/src/main/java/org/apache/ignite/examples/ml/tree/boosting/GDBOnTreesClassificationTrainerExample.java # examples/src/main/java/org/apache/ignite/examples/ml/tree/boosting/GDBOnTreesRegressionTrainerExample.java # modules/ml/src/test/java/org/apache/ignite/ml/composition/boosting/GDBTrainerTest.java
…-9412 # Conflicts: # examples/src/main/java/org/apache/ignite/examples/ml/tree/boosting/GDBOnTreesClassificationTrainerExample.java # examples/src/main/java/org/apache/ignite/examples/ml/tree/boosting/GDBOnTreesRegressionTrainerExample.java # modules/ml/src/test/java/org/apache/ignite/ml/composition/boosting/GDBTrainerTest.java
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