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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method public evaluate(dataCache Map<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,Double>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : BinaryClassificationMetricValues in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type models : List<? extends Model<Vector,Double>> to models : List<? extends IgniteModel<Vector,Double>> in method public GDBModel(models List<? extends IgniteModel<Vector,Double>>, predictionsAggregator WeightedPredictionsAggregator, internalToExternalLblMapping IgniteFunction<Double,Double>) in class org.apache.ignite.ml.composition.boosting.GDBTrainer.GDBModel |
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Change Parameter Type fitter : BiFunction<GDBTrainer,Map<Integer,double[]>,Model<Vector,Double>> to fitter : BiFunction<GDBTrainer,Map<Integer,double[]>,IgniteModel<Vector,Double>> in method private testClassifier(fitter BiFunction<GDBTrainer,Map<Integer,double[]>,IgniteModel<Vector,Double>>) : void in class org.apache.ignite.ml.composition.boosting.GDBTrainerTest |
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Change Parameter Type parser : InfModelParser<I,O,?> to parser : ModelParser<I,O,?> in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.AsyncModelBuilder |
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Change Parameter Type taskSupplier : IgniteFunction<List<DatasetTrainer<Model<IS,IA>,L>>,List<IgniteSupplier<Model<IS,IA>>>> to taskSupplier : IgniteFunction<List<DatasetTrainer<IgniteModel<IS,IA>,L>>,List<IgniteSupplier<IgniteModel<IS,IA>>>> in method private runOnSubmodels(taskSupplier IgniteFunction<List<DatasetTrainer<IgniteModel<IS,IA>,L>>,List<IgniteSupplier<IgniteModel<IS,IA>>>>, aggregatorProcessor IgniteBiFunction<DatasetTrainer<AM,L>,IgniteBiFunction<K,V,Vector>,AM>, featureExtractor IgniteBiFunction<K,V,Vector>) : StackedModel<IS,IA,O,AM> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public CacheBasedLabelPairCursor(upstreamCache IgniteCache<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, mdl IgniteModel<Vector,L>) in class org.apache.ignite.ml.selection.scoring.cursor.CacheBasedLabelPairCursor |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public LocalLabelPairCursor(upstreamMap Map<K,V>, filter IgniteBiPredicate<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, mdl IgniteModel<Vector,L>) in class org.apache.ignite.ml.selection.scoring.cursor.LocalLabelPairCursor |
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Change Parameter Type subMdl : Model<IS,IA> to subMdl : IgniteModel<IS,IA> in method package addSubmodel(subMdl IgniteModel<IS,IA>) : void in class org.apache.ignite.ml.composition.stacking.StackedModel |
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Change Parameter Type buildBaseMdlTrainer : IgniteSupplier<DatasetTrainer<? extends Model<Vector,Double>,Double>> to buildBaseMdlTrainer : IgniteSupplier<DatasetTrainer<? extends IgniteModel<Vector,Double>,Double>> in method public withBaseModelTrainerBuilder(buildBaseMdlTrainer IgniteSupplier<DatasetTrainer<? extends IgniteModel<Vector,Double>,Double>>) : GDBLearningStrategy in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Parameter Type parser : InfModelParser<I,O,?> to parser : ModelParser<I,O,?> in method package IgniteDistributedInfModelService(reader ModelReader, parser ModelParser<I,O,?>, suffix String) in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder.IgniteDistributedInfModelService |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method private calcMetricValues(dataCache Map<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,Double>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : BinaryClassificationMetricValues in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method private calculateMetric(dataCache IgniteCache<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,L>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, metric Metric<L>) : double in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type models : List<? extends Model<Vector,Double>> to models : List<? extends IgniteModel<Vector,Double>> in method public ModelsComposition(models List<? extends IgniteModel<Vector,Double>>, predictionsAggregator PredictionsAggregator) in class org.apache.ignite.ml.composition.ModelsComposition |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method public evaluate(dataCache Map<K,V>, mdl IgniteModel<Vector,Double>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : BinaryClassificationMetricValues in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type other : Model<T,W> to other : IgniteModel<T,W> in method public combine(other IgniteModel<T,W>, combiner BiFunction<V,W,X>) : IgniteModel<T,X> in class org.apache.ignite.ml.IgniteModel |
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Change Parameter Type internalMdl : Model<Vector,Double> to internalMdl : IgniteModel<Vector,Double> in method public withInternalMdl(internalMdl IgniteModel<Vector,Double>) : PipelineMdl<K,V> in class org.apache.ignite.ml.pipeline.PipelineMdl |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.AsyncModelBuilder |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public evaluate(dataCache IgniteCache<K,V>, mdl IgniteModel<Vector,L>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, metric Metric<L>) : double in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method protected updateModel(mdl IgniteModel<Vector,Double>, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : IgniteModel<Vector,Double> in class org.apache.ignite.ml.composition.BaggingTest.CountTrainer |
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Change Parameter Type mdl : Model<K,V> to mdl : IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.MLLogger |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public evaluate(dataCache Map<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,L>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, metric Metric<L>) : double in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method package IgniteDistributedInfModelService(reader ModelReader, parser ModelParser<I,O,?>, suffix String) in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder.IgniteDistributedInfModelService |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method package DistributedInfModel(ignite Ignite, suffix String, reader ModelReader, parser ModelParser<I,O,?>, instances int, maxPerNode int) in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder.DistributedInfModel |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method public ModelDescriptor(name String, desc String, signature ModelSignature, reader ModelReader, parser ModelParser<byte[],byte[],?>) in class org.apache.ignite.ml.inference.ModelDescriptor |
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Change Parameter Type models : List<Model<Vector,Double>> to models : List<IgniteModel<Vector,Double>> in method public ModelsCompositionFormat(models List<IgniteModel<Vector,Double>>, predictionsAggregator PredictionsAggregator) in class org.apache.ignite.ml.composition.ModelsCompositionFormat |
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Change Parameter Type parser : InfModelParser<I,O,?> to parser : ModelParser<I,O,?> in method package DistributedInfModel(ignite Ignite, suffix String, reader ModelReader, parser ModelParser<I,O,?>, instances int, maxPerNode int) in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder.DistributedInfModel |
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Change Parameter Type after : IgniteFunction<V,V1> to after : IgniteModel<V,V1> in method public andThen(after IgniteModel<V,V1>) : IgniteModel<T,V1> in class org.apache.ignite.ml.IgniteModel |
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Change Parameter Type mdl : Model<K,V> to mdl : IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.NoOpLogger |
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Change Parameter Type mdl : Model<K,V> to mdl : IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.CustomMLLogger |
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Change Parameter Type parser : InfModelParser<byte[],byte[],?> to parser : ModelParser<byte[],byte[],?> in method public ModelDescriptor(name String, desc String, signature ModelSignature, reader ModelReader, parser ModelParser<byte[],byte[],?>) in class org.apache.ignite.ml.inference.ModelDescriptor |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method private startService(reader ModelReader, parser ModelParser<I,O,?>, instances int, maxPerNode int) : void in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder.DistributedInfModel |
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Change Parameter Type mdl : Model<IS,IA> to mdl : IgniteModel<IS,IA> in method private applyToVector(mdl IgniteModel<IS,IA>, submodelOutput2VectorConverter IgniteFunction<IA,Vector>, vector2SubmodelInputConverter IgniteFunction<Vector,IS>, v Vector) : Vector in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Parameter Type subMdls : List<Model<IS,IA>> to subMdls : List<IgniteModel<IS,IA>> in method private getFeatureExtractorForAggregator(featureExtractor IgniteBiFunction<K,V,Vector>, subMdls List<IgniteModel<IS,IA>>, submodelInput2AggregatingInputConverter IgniteFunction<IS,IA>, submodelOutput2VectorConverter IgniteFunction<IA,Vector>, vector2SubmodelInputConverter IgniteFunction<Vector,IS>) : IgniteBiFunction<K,V,Vector> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method public evaluate(dataCache IgniteCache<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,Double>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : BinaryClassificationMetricValues in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type submodelsTrainers : List<DatasetTrainer<Model<IS,IA>,L>> to submodelsTrainers : List<DatasetTrainer<IgniteModel<IS,IA>,L>> in method public StackedDatasetTrainer(aggregatorTrainer DatasetTrainer<AM,L>, aggregatingInputMerger IgniteBinaryOperator<IA>, submodelInput2AggregatingInputConverter IgniteFunction<IS,IA>, submodelsTrainers List<DatasetTrainer<IgniteModel<IS,IA>,L>>, vector2SubmodelInputConverter IgniteFunction<Vector,IS>, submodelOutput2VectorConverter IgniteFunction<IA,Vector>) in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method private calculateMetric(dataCache Map<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,L>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, metric Metric<L>) : double in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type parser : InfModelParser<I,O,?> to parser : ModelParser<I,O,?> in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.ThreadedModelBuilder |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public evaluate(dataCache IgniteCache<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,L>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, metric Metric<L>) : double in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public evaluate(dataCache Map<K,V>, mdl IgniteModel<Vector,L>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, metric Metric<L>) : double in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type mdl : Model<Vector,L> to mdl : IgniteModel<Vector,L> in method public CacheBasedLabelPairCursor(upstreamCache IgniteCache<K,V>, filter IgniteBiPredicate<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>, mdl IgniteModel<Vector,L>) in class org.apache.ignite.ml.selection.scoring.cursor.CacheBasedLabelPairCursor |
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Change Parameter Type parser : InfModelParser<I,O,?> to parser : ModelParser<I,O,?> in method private startService(reader ModelReader, parser ModelParser<I,O,?>, instances int, maxPerNode int) : void in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder.DistributedInfModel |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method public evaluate(dataCache IgniteCache<K,V>, mdl IgniteModel<Vector,Double>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : BinaryClassificationMetricValues in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method package ModelOnFeaturesSubspace(featuresMapping Map<Integer,Integer>, mdl IgniteModel<Vector,Double>) in class org.apache.ignite.ml.composition.ModelOnFeaturesSubspace |
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Change Parameter Type mdl : Model<K,V> to mdl : IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.ConsoleLogger |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method private calcMetricValues(dataCache IgniteCache<K,V>, filter IgniteBiPredicate<K,V>, mdl IgniteModel<Vector,Double>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : BinaryClassificationMetricValues in class org.apache.ignite.ml.selection.scoring.evaluator.BinaryClassificationEvaluator |
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Change Parameter Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method protected checkState(mdl IgniteModel<Vector,Double>) : boolean in class org.apache.ignite.ml.composition.BaggingTest.CountTrainer |
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Change Parameter Type parser : InfModelParser<I,O,?> to parser : ModelParser<I,O,?> in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder |
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Change Parameter Type reader : InfModelReader to reader : ModelReader in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.ThreadedModelBuilder |
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Change Return Type Model<K,V> to IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.MLLogger |
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Change Return Type InfModelParser<byte[],byte[],?> to ModelParser<byte[],byte[],?> in method public getParser() : ModelParser<byte[],byte[],?> in class org.apache.ignite.ml.inference.ModelDescriptor |
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Change Return Type DatasetTrainer<? extends Model<Vector,Double>,Double> to DatasetTrainer<? extends IgniteModel<Vector,Double>,Double> in method protected abstract buildBaseModelTrainer() : DatasetTrainer<? extends IgniteModel<Vector,Double>,Double> in class org.apache.ignite.ml.composition.boosting.GDBTrainer |
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Change Return Type InfModel<I,Future<O>> to Model<I,Future<O>> in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilder |
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Change Return Type TensorFlowBaseInfModelParser<I,O> to TensorFlowBaseModelParser<I,O> in method public withInput(name String, transformer InputTransformer<I>) : TensorFlowBaseModelParser<I,O> in class org.apache.ignite.ml.inference.parser.TensorFlowBaseModelParser |
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Change Return Type Model<Vector,Double> to IgniteModel<Vector,Double> in method public getInternalMdl() : IgniteModel<Vector,Double> in class org.apache.ignite.ml.pipeline.PipelineMdl |
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Change Return Type List<Model<Vector,Double>> to List<IgniteModel<Vector,Double>> in method public models() : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.ModelsCompositionFormat |
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Change Return Type Model<Vector,Double> to IgniteModel<Vector,Double> in method public getMdl() : IgniteModel<Vector,Double> in class org.apache.ignite.ml.composition.ModelOnFeaturesSubspace |
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Change Return Type TensorFlowBaseInfModelParser<I,O> to TensorFlowBaseModelParser<I,O> in method public withOutput(names List<String>, transformer OutputTransformer<O>) : TensorFlowBaseModelParser<I,O> in class org.apache.ignite.ml.inference.parser.TensorFlowBaseModelParser |
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Change Return Type List<Model<Vector,Double>> to List<IgniteModel<Vector,Double>> in method public update(mdlToUpdate GDBTrainer.GDBModel, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Return Type Model<Vector,Double> to IgniteModel<Vector,Double> in method public fit(datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : IgniteModel<Vector,Double> in class org.apache.ignite.ml.composition.BaggingTest.CountTrainer |
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Change Return Type Model<K,V> to IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.CustomMLLogger |
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Change Return Type List<Model<Vector,Double>> to List<IgniteModel<Vector,Double>> in method public learnModels(datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Return Type InfModelReader to ModelReader in method public getReader() : ModelReader in class org.apache.ignite.ml.inference.ModelDescriptor |
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Change Return Type InfModel<I,Future<O>> to Model<I,Future<O>> in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.ThreadedModelBuilder |
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Change Return Type InfModel<I,O> to Model<I,O> in method public parse(mdl byte[]) : Model<I,O> in class org.apache.ignite.ml.inference.parser.TensorFlowBaseModelParser |
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Change Return Type Model<T,X> to IgniteModel<T,X> in method public combine(other IgniteModel<T,W>, combiner BiFunction<V,W,X>) : IgniteModel<T,X> in class org.apache.ignite.ml.IgniteModel |
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Change Return Type InfModel<I,O> to IgniteModel<I,O> in method public parse(mdl byte[]) : IgniteModel<I,O> in class org.apache.ignite.ml.inference.parser.IgniteModelParser |
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Change Return Type Model<K,V> to IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.ConsoleLogger |
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Change Return Type Model<K,V> to IgniteModel<K,V> in method public log(verboseLevel VerboseLevel, mdl IgniteModel<K,V>) : IgniteModel<K,V> in class org.apache.ignite.ml.environment.logging.NoOpLogger |
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Change Return Type List<Model<Vector,Double>> to List<IgniteModel<Vector,Double>> in method public update(mdlToUpdate GDBTrainer.GDBModel, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.tree.boosting.GDBOnTreesLearningStrategy |
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Change Return Type InfModel<I,Future<O>> to Model<I,Future<O>> in method public build(reader ModelReader, parser ModelParser<I,O,?>) : Model<I,Future<O>> in class org.apache.ignite.ml.inference.builder.AsyncModelBuilder |
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Change Return Type Model<T,V> to IgniteModel<T,V> in method public constantModel(v V) : IgniteModel<T,V> in class org.apache.ignite.ml.TestUtils |
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Change Return Type Model<Vector,Double> to IgniteModel<Vector,Double> in method protected updateModel(mdl IgniteModel<Vector,Double>, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : IgniteModel<Vector,Double> in class org.apache.ignite.ml.composition.BaggingTest.CountTrainer |
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Change Return Type List<Model<Vector,Double>> to List<IgniteModel<Vector,Double>> in method public getModels() : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.ModelsComposition |
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Change Return Type InfModelParser<Integer,Integer,InfModel<Integer,Integer>> to ModelParser<Integer,Integer,Model<Integer,Integer>> in method package getParser() : ModelParser<Integer,Integer,Model<Integer,Integer>> in class org.apache.ignite.ml.inference.builder.ModelBuilderTestUtil |
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Change Return Type List<Model<IS,IA>> to List<IgniteModel<IS,IA>> in method package submodels() : List<IgniteModel<IS,IA>> in class org.apache.ignite.ml.composition.stacking.StackedModel |
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Change Return Type InfModelReader to ModelReader in method package getReader() : ModelReader in class org.apache.ignite.ml.inference.builder.ModelBuilderTestUtil |
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Change Return Type List<Model<Vector,Double>> to List<IgniteModel<Vector,Double>> in method protected initLearningState(mdlToUpdate GDBTrainer.GDBModel) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Return Type Model<T,V1> to IgniteModel<T,V1> in method public andThen(after IgniteModel<V,V1>) : IgniteModel<T,V1> in class org.apache.ignite.ml.IgniteModel |
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Change Variable Type res : List<IgniteSupplier<Model<IS,IA>>> to res : List<IgniteSupplier<IgniteModel<IS,IA>>> in method public update(mdl StackedModel<IS,IA,O,AM>, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>) : StackedModel<IS,IA,O,AM> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type parser : InfModelParser<Vector,Double,?> to parser : ModelParser<Vector,Double,?> in method public main(args String...) : void in class org.apache.ignite.examples.ml.inference.IgniteModelDistributedInferenceExample |
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Change Variable Type trainer : StackedDatasetTrainer<Void,Void,Void,Model<Void,Void>,Void> to trainer : StackedDatasetTrainer<Void,Void,Void,IgniteModel<Void,Void>,Void> in method public testINoWaysOfPropagation() : void in class org.apache.ignite.ml.composition.StackingTest |
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Change Variable Type reader : InfModelReader to reader : ModelReader in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowLocalInferenceExample |
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Change Variable Type parser : InfModelParser<double[],Long,?> to parser : ModelParser<double[],Long,?> in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowDistributedInferenceExample |
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Change Variable Type reader : InfModelReader to reader : ModelReader in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowThreadedInferenceExample |
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Change Variable Type models : List<Model<Vector,Double>> to models : List<IgniteModel<Vector,Double>> in method public update(mdlToUpdate GDBTrainer.GDBModel, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Variable Type oldModels : ArrayList<Model<Vector,Double>> to oldModels : ArrayList<IgniteModel<Vector,Double>> in method protected updateModel(mdl ModelsComposition, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : ModelsComposition in class org.apache.ignite.ml.tree.randomforest.RandomForestTrainer |
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Change Variable Type mdl : Model<Object,Vector> to mdl : IgniteModel<Object,Vector> in method public testRandomNumbersGenerator() : void in class org.apache.ignite.ml.environment.LearningEnvironmentTest |
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Change Variable Type mdl : InfModel<HashMap<String,Double>,Future<Double>> to mdl : Model<HashMap<String,Double>,Future<Double>> in method public main(args String...) : void in class org.apache.ignite.examples.ml.xgboost.XGBoostModelParserExample |
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Change Variable Type trainer1 : DatasetTrainer<Model<IS,IA>,L> to trainer1 : DatasetTrainer<IgniteModel<IS,IA>,L> in method public addTrainer(trainer DatasetTrainer<M1,L>) : StackedDatasetTrainer<IS,IA,O,AM,L> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type infMdl : InfModel<Vector,Future<Double>> to infMdl : Model<Vector,Future<Double>> in method public main(args String...) : void in class org.apache.ignite.examples.ml.inference.IgniteModelDistributedInferenceExample |
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Change Variable Type mdlBuilder : AsyncInfModelBuilder to mdlBuilder : AsyncModelBuilder in method public main(args String...) : void in class org.apache.ignite.examples.ml.xgboost.XGBoostModelParserExample |
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Change Variable Type parser : InfModelParser<double[],Long,?> to parser : ModelParser<double[],Long,?> in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowThreadedInferenceExample |
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Change Variable Type trainer : DatasetTrainer<Model<Object,Vector>,Void> to trainer : DatasetTrainer<IgniteModel<Object,Vector>,Void> in method public testRandomNumbersGenerator() : void in class org.apache.ignite.ml.environment.LearningEnvironmentTest |
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Change Variable Type infMdl : InfModel<Integer,Future<Integer>> to infMdl : Model<Integer,Future<Integer>> in method public testBuild() : void in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilderTest |
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Change Variable Type reader : InfModelReader to reader : ModelReader in method public main(args String...) : void in class org.apache.ignite.examples.ml.inference.IgniteModelDistributedInferenceExample |
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Change Variable Type infMdl : InfModel<byte[],byte[]> to infMdl : Model<byte[],byte[]> in method public main(args String...) : void in class org.apache.ignite.examples.ml.inference.ModelStorageExample |
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Change Variable Type function : IgniteFunction<I,O> to res : IgniteModel<I,O> in method public parse(mdl byte[]) : IgniteModel<I,O> in class org.apache.ignite.ml.inference.parser.IgniteModelParser |
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Change Variable Type models : List<Model<Vector,Double>> to models : List<IgniteModel<Vector,Double>> in method public update(mdlToUpdate GDBTrainer.GDBModel, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.tree.boosting.GDBOnTreesLearningStrategy |
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Change Variable Type subMdls : List<Model<IS,IA>> to subMdls : List<IgniteModel<IS,IA>> in method private runOnSubmodels(taskSupplier IgniteFunction<List<DatasetTrainer<IgniteModel<IS,IA>,L>>,List<IgniteSupplier<IgniteModel<IS,IA>>>>, aggregatorProcessor IgniteBiFunction<DatasetTrainer<AM,L>,IgniteBiFunction<K,V,Vector>,AM>, featureExtractor IgniteBiFunction<K,V,Vector>) : StackedModel<IS,IA,O,AM> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type mdlBuilder : SingleInfModelBuilder to mdlBuilder : SingleModelBuilder in method public main(args String...) : void in class org.apache.ignite.examples.ml.inference.ModelStorageExample |
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Change Variable Type reader : InfModelReader to reader : ModelReader in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowDistributedInferenceExample |
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Change Variable Type mdlBuilder : AsyncInfModelBuilder to mdlBuilder : AsyncModelBuilder in method public testBuild() : void in class org.apache.ignite.ml.inference.builder.ThreadedModelBuilderTest |
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Change Variable Type internalMdl : Model<Vector,Double> to internalMdl : IgniteModel<Vector,Double> in method private fit(datasetBuilder DatasetBuilder) : PipelineMdl<K,V> in class org.apache.ignite.ml.pipeline.Pipeline |
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Change Variable Type models : List<Model<Vector,Double>> to models : List<IgniteModel<Vector,Double>> in method protected initLearningState(mdlToUpdate GDBTrainer.GDBModel) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Variable Type reader : InfModelReader to reader : ModelReader in method public testParseAndPredict() : void in class org.apache.ignite.ml.xgboost.parser.XGBoostModelParserTest |
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Change Variable Type locMdl : InfModel<double[],Long> to locMdl : Model<double[],Long> in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowLocalInferenceExample |
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Change Variable Type mdlSuppliers : List<IgniteSupplier<Model<IS,IA>>> to mdlSuppliers : List<IgniteSupplier<IgniteModel<IS,IA>>> in method private runOnSubmodels(taskSupplier IgniteFunction<List<DatasetTrainer<IgniteModel<IS,IA>,L>>,List<IgniteSupplier<IgniteModel<IS,IA>>>>, aggregatorProcessor IgniteBiFunction<DatasetTrainer<AM,L>,IgniteBiFunction<K,V,Vector>,AM>, featureExtractor IgniteBiFunction<K,V,Vector>) : StackedModel<IS,IA,O,AM> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type subMdl : Model<IS,IA> to subMdl : IgniteModel<IS,IA> in method private runOnSubmodels(taskSupplier IgniteFunction<List<DatasetTrainer<IgniteModel<IS,IA>,L>>,List<IgniteSupplier<IgniteModel<IS,IA>>>>, aggregatorProcessor IgniteBiFunction<DatasetTrainer<AM,L>,IgniteBiFunction<K,V,Vector>,AM>, featureExtractor IgniteBiFunction<K,V,Vector>) : StackedModel<IS,IA,O,AM> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type infMdl : InfModel<Integer,Integer> to infMdl : Model<Integer,Integer> in method public testBuild() : void in class org.apache.ignite.ml.inference.builder.SingleModelBuilderTest |
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Change Variable Type infMdl : InfModel<Integer,Future<Integer>> to infMdl : Model<Integer,Future<Integer>> in method public testBuild() : void in class org.apache.ignite.ml.inference.builder.ThreadedModelBuilderTest |
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Change Variable Type mdlBuilder : AsyncInfModelBuilder to mdlBuilder : AsyncModelBuilder in method public testBuild() : void in class org.apache.ignite.ml.inference.builder.IgniteDistributedModelBuilderTest |
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Change Variable Type mdlBuilder : SyncInfModelBuilder to mdlBuilder : SyncModelBuilder in method public testBuild() : void in class org.apache.ignite.ml.inference.builder.SingleModelBuilderTest |
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Change Variable Type threadedMdl : InfModel<double[],Future<Long>> to threadedMdl : Model<double[],Future<Long>> in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowThreadedInferenceExample |
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Change Variable Type parser : InfModelParser<double[],Long,?> to parser : ModelParser<double[],Long,?> in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowLocalInferenceExample |
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Change Variable Type trainer : DatasetTrainer<? extends Model<Vector,Double>,Double> to trainer : DatasetTrainer<? extends IgniteModel<Vector,Double>,Double> in method public update(mdlToUpdate GDBTrainer.GDBModel, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.composition.boosting.GDBLearningStrategy |
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Change Variable Type threadedMdl : InfModel<double[],Future<Long>> to threadedMdl : Model<double[],Future<Long>> in method public main(args String[]) : void in class org.apache.ignite.examples.ml.inference.TensorFlowDistributedInferenceExample |
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Change Variable Type mdl : Model<Object,Object> to mdl : IgniteModel<Object,Object> in method public testCombine() : void in class org.apache.ignite.ml.common.ModelTest |
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Change Variable Type models : List<Model<Vector,Double>> to models : List<IgniteModel<Vector,Double>> in method protected updateModel(mdl ModelsComposition, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : ModelsComposition in class org.apache.ignite.ml.composition.boosting.GDBTrainer |
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Change Variable Type trainer : DatasetTrainer<Model<IS,IA>,L> to trainer : DatasetTrainer<IgniteModel<IS,IA>,L> in method public update(mdl StackedModel<IS,IA,O,AM>, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,L>) : StackedModel<IS,IA,O,AM> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type reader : InfModelReader to reader : ModelReader in method public main(args String...) : void in class org.apache.ignite.examples.ml.xgboost.XGBoostModelParserExample |
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Change Variable Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method private testClassifier(fitter BiFunction<GDBTrainer,Map<Integer,double[]>,IgniteModel<Vector,Double>>) : void in class org.apache.ignite.ml.composition.boosting.GDBTrainerTest |
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Change Variable Type mdl : Model<IS,IA> to mdl : IgniteModel<IS,IA> in method public addTrainer(trainer DatasetTrainer<M1,L>) : StackedDatasetTrainer<IS,IA,O,AM,L> in class org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer |
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Change Variable Type trainer : DatasetTrainer<? extends Model<Vector,Double>,Double> to trainer : DatasetTrainer<? extends IgniteModel<Vector,Double>,Double> in method public update(mdlToUpdate GDBTrainer.GDBModel, datasetBuilder DatasetBuilder<K,V>, featureExtractor IgniteBiFunction<K,V,Vector>, lbExtractor IgniteBiFunction<K,V,Double>) : List<IgniteModel<Vector,Double>> in class org.apache.ignite.ml.tree.boosting.GDBOnTreesLearningStrategy |
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Change Variable Type mdl : Model<Vector,Double> to mdl : IgniteModel<Vector,Double> in method public testFitRegression() : void in class org.apache.ignite.ml.composition.boosting.GDBTrainerTest |
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