diff --git a/checkstyle/checkstyle-suppressions.xml b/checkstyle/checkstyle-suppressions.xml index 250e0fa411f10..20c95378d0a91 100644 --- a/checkstyle/checkstyle-suppressions.xml +++ b/checkstyle/checkstyle-suppressions.xml @@ -24,4 +24,6 @@ + diff --git a/checkstyle/checkstyle.xml b/checkstyle/checkstyle.xml index 3e674bda23444..87b156c1f221f 100644 --- a/checkstyle/checkstyle.xml +++ b/checkstyle/checkstyle.xml @@ -135,4 +135,12 @@ --> + + + + + diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/clustering/KMeansClusterizationExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/clustering/KMeansClusterizationExample.java index 3127418f9653f..b834529280fbd 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/clustering/KMeansClusterizationExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/clustering/KMeansClusterizationExample.java @@ -62,7 +62,8 @@ public static void main(String[] args) throws IOException { try { dataCache = new SandboxMLCache(ignite).fillCacheWith(MLSandboxDatasets.TWO_CLASSED_IRIS); - Vectorizer vectorizer = new DummyVectorizer().labeled(Vectorizer.LabelCoordinate.FIRST); + Vectorizer vectorizer = + new DummyVectorizer().labeled(Vectorizer.LabelCoordinate.FIRST); KMeansTrainer trainer = new KMeansTrainer(); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/dataset/AlgorithmSpecificDatasetExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/dataset/AlgorithmSpecificDatasetExample.java index 731227f093b5e..85102f42242ff 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/dataset/AlgorithmSpecificDatasetExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/dataset/AlgorithmSpecificDatasetExample.java @@ -80,7 +80,8 @@ public static void main(String[] args) throws Exception { Vectorizer vectorizer = new DummyVectorizer<>(1); - IgniteFunction, LabeledVector> func = lv -> new LabeledVector<>(lv.features(), new double[] {lv.label()}); + IgniteFunction, LabeledVector> func = + lv -> new LabeledVector<>(lv.features(), new double[] {lv.label()}); //NOTE: This class is part of Developer API and all lambdas should be loaded on server manually. Preprocessor preprocessor = new PatchedPreprocessor<>(func, vectorizer); @@ -89,18 +90,19 @@ public static void main(String[] args) throws Exception { SimpleLabeledDatasetDataBuilder builder = new SimpleLabeledDatasetDataBuilder<>(preprocessor); - IgniteBiFunction builderFun = (data, ctx) -> { - double[] features = data.getFeatures(); - int rows = data.getRows(); + IgniteBiFunction builderFun = + (data, ctx) -> { + double[] features = data.getFeatures(); + int rows = data.getRows(); - // Makes a copy of features to supplement it by columns with values equal to 1.0. - double[] a = new double[features.length + rows]; - Arrays.fill(a, 1.0); + // Makes a copy of features to supplement it by columns with values equal to 1.0. + double[] a = new double[features.length + rows]; + Arrays.fill(a, 1.0); - System.arraycopy(features, 0, a, rows, features.length); + System.arraycopy(features, 0, a, rows, features.length); - return new SimpleLabeledDatasetData(a, data.getLabels(), rows); - }; + return new SimpleLabeledDatasetData(a, data.getLabels(), rows); + }; try (AlgorithmSpecificDataset dataset = DatasetFactory.create( ignite, diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/catboost/CatboostClassificationModelParserExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/catboost/CatboostClassificationModelParserExample.java index e6f9f657a8a18..093469a6069e9 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/catboost/CatboostClassificationModelParserExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/catboost/CatboostClassificationModelParserExample.java @@ -53,7 +53,8 @@ public class CatboostClassificationModelParserExample { /** * Test expected results. */ - private static final String TEST_ER_RES = "examples/src/main/resources/datasets/amazon-employee-access-challenge-sample-catboost-expected-results.csv"; + private static final String TEST_ER_RES = + "examples/src/main/resources/datasets/amazon-employee-access-challenge-sample-catboost-expected-results.csv"; /** * Parser. diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/exchange/KMeansClusterizationExportImportExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/exchange/KMeansClusterizationExportImportExample.java index ec5e6899f7eab..f841a06e593c9 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/exchange/KMeansClusterizationExportImportExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/exchange/KMeansClusterizationExportImportExample.java @@ -62,7 +62,8 @@ public static void main(String[] args) throws IOException { try { dataCache = new SandboxMLCache(ignite).fillCacheWith(MLSandboxDatasets.TWO_CLASSED_IRIS); - Vectorizer vectorizer = new DummyVectorizer().labeled(Vectorizer.LabelCoordinate.FIRST); + Vectorizer vectorizer = + new DummyVectorizer().labeled(Vectorizer.LabelCoordinate.FIRST); KMeansTrainer trainer = new KMeansTrainer() .withDistance(new WeightedMinkowskiDistance(2, new double[] {5.9360, 2.7700, 4.2600, 1.3260})); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java index d03bb966f6a7d..41717ba9bcb48 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeFromSparkExample.java @@ -50,15 +50,18 @@ public class DecisionTreeFromSparkExample { .toPath().toAbsolutePath().toString(); /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Decision Tree model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Decision Tree model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeRegressionFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeRegressionFromSparkExample.java index 5fd446140f38a..f0e95fdb92ee2 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeRegressionFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/DecisionTreeRegressionFromSparkExample.java @@ -50,15 +50,18 @@ public class DecisionTreeRegressionFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/dtreg"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Decision tree regression model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Decision tree regression model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTFromSparkExample.java index 1fc72fa8d898c..4154f24695d0f 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTFromSparkExample.java @@ -48,15 +48,18 @@ public class GBTFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/gbt"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Gradient Boosted trees model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Gradient Boosted trees model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java index ee3e8bf9f2c81..561ab9c7bfa79 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/GBTRegressionFromSparkExample.java @@ -50,15 +50,18 @@ public class GBTRegressionFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/gbtreg"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> GBT Regression model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> GBT Regression model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/KMeansFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/KMeansFromSparkExample.java index 3ac8b64b7af59..5aa6527329652 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/KMeansFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/KMeansFromSparkExample.java @@ -50,8 +50,9 @@ public class KMeansFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/kmeans"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LinearRegressionFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LinearRegressionFromSparkExample.java index b799d403f47a2..52842aac1c2cd 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LinearRegressionFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LinearRegressionFromSparkExample.java @@ -50,15 +50,17 @@ public class LinearRegressionFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/linreg"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Linear regression model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Linear regression model loaded from Spark through serialization over partitioned dataset usage example started."); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LogRegFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LogRegFromSparkExample.java index 4a4df17ec3c9b..725ac3873ee62 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LogRegFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/LogRegFromSparkExample.java @@ -48,15 +48,18 @@ public class LogRegFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/logreg"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Logistic regression model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Logistic regression model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestFromSparkExample.java index 404ad840f5c64..641285dded444 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestFromSparkExample.java @@ -48,15 +48,18 @@ public class RandomForestFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/rf"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Random Forest model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Random Forest model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestRegressionFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestRegressionFromSparkExample.java index 5f535f104e160..c1b8babd7a1b9 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestRegressionFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/RandomForestRegressionFromSparkExample.java @@ -50,15 +50,18 @@ public class RandomForestRegressionFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/rfreg"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. */ public static void main(String[] args) throws FileNotFoundException { System.out.println(); - System.out.println(">>> Random Forest regression model loaded from Spark through serialization over partitioned dataset usage example started."); + System.out.println( + ">>> Random Forest regression model loaded from Spark through serialization over partitioned dataset usage example started." + ); // Start ignite grid. try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) { System.out.println(">>> Ignite grid started."); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/SVMFromSparkExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/SVMFromSparkExample.java index d66e8820794d2..adcab7a020708 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/SVMFromSparkExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/inference/spark/modelparser/SVMFromSparkExample.java @@ -48,8 +48,9 @@ public class SVMFromSparkExample { public static final String SPARK_MDL_PATH = "examples/src/main/resources/models/spark/serialized/svm"; /** Learning environment. */ - public static final LearningEnvironment env = LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) - .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); + public static final LearningEnvironment env = + LearningEnvironmentBuilder.defaultBuilder().withParallelismStrategyTypeDependency(ParallelismStrategy.ON_DEFAULT_POOL) + .withLoggingFactoryDependency(ConsoleLogger.Factory.HIGH).buildForTrainer(); /** * Run example. diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/multiclass/OneVsRestClassificationExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/multiclass/OneVsRestClassificationExample.java index dd5fecf941263..14b05c4890f97 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/multiclass/OneVsRestClassificationExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/multiclass/OneVsRestClassificationExample.java @@ -145,7 +145,12 @@ public static void main(String[] args) throws IOException { confusionMtxWithMinMaxScaling[idx1][idx2]++; - System.out.printf(">>> | %.4f\t\t| %.4f\t\t\t\t\t\t| %.4f\t\t|\n", prediction, predictionWithMinMaxScaling, groundTruth); + System.out.printf( + ">>> | %.4f\t\t| %.4f\t\t\t\t\t\t| %.4f\t\t|\n", + prediction, + predictionWithMinMaxScaling, + groundTruth + ); } System.out.println(">>> ----------------------------------------------------------------"); System.out.println("\n>>> -----------------One-vs-Rest SVM model-------------"); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/preprocessing/encoding/TargetEncoderExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/preprocessing/encoding/TargetEncoderExample.java index e3864b6721d79..82089acd8a035 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/preprocessing/encoding/TargetEncoderExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/preprocessing/encoding/TargetEncoderExample.java @@ -71,8 +71,8 @@ public static void main(String[] args) { Set targetEncodedfeaturesIndexies = new HashSet<>(Arrays.asList(1, 5, 6)); Integer targetIndex = 0; - final Vectorizer vectorizer = new ObjectArrayVectorizer(featuresIndexies.toArray(new Integer[0])) - .labeled(targetIndex); + final Vectorizer vectorizer = + new ObjectArrayVectorizer(featuresIndexies.toArray(new Integer[0])).labeled(targetIndex); Preprocessor strEncoderPreprocessor = new EncoderTrainer() .withEncoderType(EncoderType.STRING_ENCODER) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/BostonHousePricesPredictionExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/BostonHousePricesPredictionExample.java index c572d81038741..9d2b31683c84e 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/BostonHousePricesPredictionExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/BostonHousePricesPredictionExample.java @@ -42,7 +42,8 @@ * Description of model can be found in: https://en.wikipedia.org/wiki/Linear_regression . Original dataset can be * downloaded from: https://archive.ics.uci.edu/ml/machine-learning-databases/housing/ . Copy of dataset are stored in: * modules/ml/src/main/resources/datasets/boston_housing_dataset.txt . Score for regression estimation: R^2 (coefficient - * of determination). Description of score evaluation can be found in: https://stattrek.com/statistics/dictionary.aspx?definition=coefficient_of_determination + * of determination). Description of score evaluation can be found in: + * https://stattrek.com/statistics/dictionary.aspx?definition=coefficient_of_determination * . */ public class BostonHousePricesPredictionExample { diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/LinearRegressionLSQRTrainerWithMinMaxScalerExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/LinearRegressionLSQRTrainerWithMinMaxScalerExample.java index 9979d3c0215ee..35dbdcd791709 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/LinearRegressionLSQRTrainerWithMinMaxScalerExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/regression/linear/LinearRegressionLSQRTrainerWithMinMaxScalerExample.java @@ -92,7 +92,9 @@ public static void main(String[] args) throws IOException { System.out.println("\n>>> Rmse = " + rmse); System.out.println(">>> ---------------------------------"); - System.out.println(">>> Linear regression model with MinMaxScaler preprocessor over cache based dataset usage example completed."); + System.out.println( + ">>> Linear regression model with MinMaxScaler preprocessor over cache based dataset usage example completed." + ); } finally { if (dataCache != null) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/sql/DecisionTreeClassificationTrainerSQLInferenceExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/sql/DecisionTreeClassificationTrainerSQLInferenceExample.java index 68058b75b9eb3..9847288350c02 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/sql/DecisionTreeClassificationTrainerSQLInferenceExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/sql/DecisionTreeClassificationTrainerSQLInferenceExample.java @@ -118,8 +118,8 @@ public static void main(String[] args) throws IOException { System.out.println("Inference..."); try (QueryCursor> cursor = cache.query(new SqlFieldsQuery("select " + "survived as truth, " + - "predict('titanic_model_tree', pclass, age, sibsp, parch, fare, case sex when 'male' then 1 else 0 end) as prediction " + - "from titanic_train"))) { + "predict('titanic_model_tree', pclass, age, sibsp, parch, fare, case sex when 'male' then 1 else 0 end) as prediction" + + " from titanic_train"))) { // Print inference result. System.out.println("| Truth | Prediction |"); System.out.println("|--------------------|"); diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestClassificationExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestClassificationExample.java index 0d9dbef8c40fa..07657c383277f 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestClassificationExample.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestClassificationExample.java @@ -108,7 +108,9 @@ public static void main(String[] args) throws IOException { System.out.println("\n>>> Absolute amount of errors " + amountOfErrors); System.out.println("\n>>> Accuracy " + (1 - amountOfErrors / (double)totalAmount)); - System.out.println(">>> Random Forest multi-class classification algorithm over cached dataset usage example completed."); + System.out.println( + ">>> Random Forest multi-class classification algorithm over cached dataset usage example completed." + ); } } diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_13_RandomSearch.java b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_13_RandomSearch.java index c489fc962bba7..445a6496ebc6a 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_13_RandomSearch.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_13_RandomSearch.java @@ -134,7 +134,11 @@ public static void main(String[] args) { ) .addHyperParam("p", normalizationTrainer::withP, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) .addHyperParam("maxDeep", trainerCV::withMaxDeep, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) - .addHyperParam("minImpurityDecrease", trainerCV::withMinImpurityDecrease, new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0}); + .addHyperParam( + "minImpurityDecrease", + trainerCV::withMinImpurityDecrease, + new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0} + ); scoreCalculator .withIgnite(ignite) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_14_Parallel_Brute_Force_Search.java b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_14_Parallel_Brute_Force_Search.java index b63bf9643be63..0acfa8afd009e 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_14_Parallel_Brute_Force_Search.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_14_Parallel_Brute_Force_Search.java @@ -133,7 +133,11 @@ public static void main(String[] args) { .withParameterSearchStrategy(new BruteForceStrategy()) .addHyperParam("p", normalizationTrainer::withP, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) .addHyperParam("maxDeep", trainerCV::withMaxDeep, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) - .addHyperParam("minImpurityDecrease", trainerCV::withMinImpurityDecrease, new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0}); + .addHyperParam( + "minImpurityDecrease", + trainerCV::withMinImpurityDecrease, + new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0} + ); scoreCalculator .withIgnite(ignite) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_15_Parallel_Random_Search.java b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_15_Parallel_Random_Search.java index ac6c1eb3c988a..c500cbd955a77 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_15_Parallel_Random_Search.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_15_Parallel_Random_Search.java @@ -136,7 +136,11 @@ public static void main(String[] args) { ) .addHyperParam("p", normalizationTrainer::withP, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) .addHyperParam("maxDeep", trainerCV::withMaxDeep, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) - .addHyperParam("minImpurityDecrease", trainerCV::withMinImpurityDecrease, new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0}); + .addHyperParam( + "minImpurityDecrease", + trainerCV::withMinImpurityDecrease, + new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0} + ); scoreCalculator .withIgnite(ignite) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_16_Genetic_Programming_Search.java b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_16_Genetic_Programming_Search.java index 408eb48289c21..9a78a8b03b1ed 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_16_Genetic_Programming_Search.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_16_Genetic_Programming_Search.java @@ -130,7 +130,11 @@ public static void main(String[] args) { .withParameterSearchStrategy(new EvolutionOptimizationStrategy()) .addHyperParam("p", normalizationTrainer::withP, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) .addHyperParam("maxDeep", trainerCV::withMaxDeep, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) - .addHyperParam("minImpurityDecrease", trainerCV::withMinImpurityDecrease, new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0}); + .addHyperParam( + "minImpurityDecrease", + trainerCV::withMinImpurityDecrease, + new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0} + ); scoreCalculator .withIgnite(ignite) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_17_Parallel_Genetic_Programming_Search.java b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_17_Parallel_Genetic_Programming_Search.java index a9d39bd309219..eee4f8c3e78bd 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_17_Parallel_Genetic_Programming_Search.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/tutorial/hyperparametertuning/Step_17_Parallel_Genetic_Programming_Search.java @@ -133,7 +133,11 @@ public static void main(String[] args) { .withParameterSearchStrategy(new EvolutionOptimizationStrategy()) .addHyperParam("p", normalizationTrainer::withP, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) .addHyperParam("maxDeep", trainerCV::withMaxDeep, new Double[] {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}) - .addHyperParam("minImpurityDecrease", trainerCV::withMinImpurityDecrease, new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0}); + .addHyperParam( + "minImpurityDecrease", + trainerCV::withMinImpurityDecrease, + new Double[] {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0} + ); scoreCalculator .withIgnite(ignite) diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java b/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java index 9f706599af012..74704ff6a8a48 100644 --- a/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java +++ b/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java @@ -52,7 +52,10 @@ public enum MLSandboxDatasets { /** The Wine recognition data. Could be found here. */ WINE_RECOGNITION("examples/src/main/resources/datasets/wine.txt", false, ","), - /** The Boston house-prices dataset. Could be found here. */ + /** + * The Boston house-prices dataset. + * Could be found here. + */ BOSTON_HOUSE_PRICES("examples/src/main/resources/datasets/boston_housing_dataset.txt", false, ","), /** Example from book Barber D. Bayesian reasoning and machine learning. Chapter 10. */ @@ -61,7 +64,9 @@ public enum MLSandboxDatasets { /** Wholesale customers dataset. Could be found here. */ WHOLESALE_CUSTOMERS("examples/src/main/resources/datasets/wholesale_customers.csv", true, ","), - /** Fraud detection problem [part of whole dataset]. Could be found here. */ + /** + * Fraud detection problem [part of whole dataset]. Could be found here. + */ FRAUD_DETECTION("examples/src/main/resources/datasets/fraud_detection.csv", false, ","), /** A dataset with discrete and continuous features. */ diff --git a/examples/src/main/spark/org/apache/ignite/examples/spark/JavaIgniteDataFrameJoinExample.java b/examples/src/main/spark/org/apache/ignite/examples/spark/JavaIgniteDataFrameJoinExample.java index f077e1a6a4563..b0a4db6c38403 100644 --- a/examples/src/main/spark/org/apache/ignite/examples/spark/JavaIgniteDataFrameJoinExample.java +++ b/examples/src/main/spark/org/apache/ignite/examples/spark/JavaIgniteDataFrameJoinExample.java @@ -120,7 +120,9 @@ private static void nativeSparkSqlJoinExample(SparkSession spark) { cities.createOrReplaceTempView("city"); // Selecting data from Ignite through Spark SQL Engine. - Dataset joinResult = spark.sql("SELECT person.name AS person, age, city.name AS city, country FROM person JOIN city ON person.city_id = city.id"); + Dataset joinResult = spark.sql( + "SELECT person.name AS person, age, city.name AS city, country FROM person JOIN city ON person.city_id = city.id" + ); joinResult.explain(true); joinResult.printSchema(); diff --git a/idea/ignite_codeStyle.xml b/idea/ignite_codeStyle.xml index 5cbce884b3f71..8004e250df990 100644 --- a/idea/ignite_codeStyle.xml +++ b/idea/ignite_codeStyle.xml @@ -13,6 +13,7 @@ +