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org.apache.ignite.ml.trainers.FeatureLabelExtractor to org.apache.ignite.ml.dataset.feature.extractor.Vectorizer
No. of Instances - 56
No. of Commits - 1
No. of Projects - {'ignite'}
Hierarchy/Composition: T_SUPER_R
Primitive Info: -
NameSpace: Internal -> Internal
Mapping:
Add or Remove Method invocation
KNNUtils.buildDataset(envBuilder,datasetBuilder,CompositionUtils.asFeatureExtractor(extractor),CompositionUtils.asLabelExtractor(extractor))
to
KNNUtils.buildDataset(envBuilder,datasetBuilder,extractor)
extractor.andThen(mapping)
to
extractor.map(mapping)
learnLabels(datasetBuilder,CompositionUtils.asFeatureExtractor(extractor),CompositionUtils.asLabelExtractor(extractor))
to
learnLabels(datasetBuilder,extractor)
trainers.get(j).update(typedMdl.submodels().get(j),datasetBuilder,CompositionUtils.asFeatureExtractor(extractor),CompositionUtils.asLabelExtractor(extractor))
to
trainers.get(j).update(typedMdl.submodels().get(j),datasetBuilder,extractor)
trainers.stream().map(tr -> (IgniteSupplier<IgniteModel<I,O>>)(() -> tr.fit(datasetBuilder,CompositionUtils.asFeatureExtractor(extractor),CompositionUtils.asLabelExtractor(extractor))))
to
trainers.stream().map(tr -> (IgniteSupplier<IgniteModel<I,O>>)(() -> tr.fit(datasetBuilder,extractor)))
tr.fit(datasetBuilder,extractor.andThen(mapping))
to
tr.fit(datasetBuilder,extractor.map(mapping))
extractor.andThen(afterExtractor)
to
extractor.map(afterExtractor)
extractor.andThen(mapping)
to
extractor.map(mapping)
KNNUtils.buildDataset(envBuilder,datasetBuilder,CompositionUtils.asFeatureExtractor(extractor),CompositionUtils.asLabelExtractor(extractor))
to
KNNUtils.buildDataset(envBuilder,datasetBuilder,extractor)
extractor.andThen(afterExtractor)
to
extractor.map(afterExtractor)
Rename Variable
extractor
to
vectorizer
Update Class Instacne Creation
new SimpleLabeledDatasetDataBuilder<>(CompositionUtils.asFeatureExtractor(extractor),CompositionUtils.asLabelExtractor(extractor))
to
new SimpleLabeledDatasetDataBuilder<>(extractor)