Package

org.apache.spark.examples

ml

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package ml

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Type Members

  1. case class Document(id: Long, text: String) extends Product with Serializable

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    Annotations
    @BeanInfo()
  2. class JavaAFTSurvivalRegressionExample extends AnyRef

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  3. class JavaALSExample extends AnyRef

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  4. class JavaBinarizerExample extends AnyRef

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  5. class JavaBisectingKMeansExample extends AnyRef

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  6. class JavaBucketizerExample extends AnyRef

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  7. class JavaChiSqSelectorExample extends AnyRef

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  8. class JavaCountVectorizerExample extends AnyRef

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  9. class JavaDCTExample extends AnyRef

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  10. class JavaDecisionTreeClassificationExample extends AnyRef

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  11. class JavaDecisionTreeRegressionExample extends AnyRef

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  12. class JavaDocument extends Serializable

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  13. class JavaElementwiseProductExample extends AnyRef

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  14. class JavaEstimatorTransformerParamExample extends AnyRef

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  15. class JavaGaussianMixtureExample extends AnyRef

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  16. class JavaGeneralizedLinearRegressionExample extends AnyRef

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  17. class JavaGradientBoostedTreeClassifierExample extends AnyRef

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  18. class JavaGradientBoostedTreeRegressorExample extends AnyRef

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  19. class JavaIndexToStringExample extends AnyRef

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  20. class JavaIsotonicRegressionExample extends AnyRef

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  21. class JavaKMeansExample extends AnyRef

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  22. class JavaLDAExample extends AnyRef

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  23. class JavaLabeledDocument extends JavaDocument with Serializable

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  24. class JavaLinearRegressionWithElasticNetExample extends AnyRef

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  25. class JavaLogisticRegressionSummaryExample extends AnyRef

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  26. class JavaLogisticRegressionWithElasticNetExample extends AnyRef

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  27. class JavaMaxAbsScalerExample extends AnyRef

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  28. class JavaMinMaxScalerExample extends AnyRef

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  29. class JavaModelSelectionViaCrossValidationExample extends AnyRef

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  30. class JavaModelSelectionViaTrainValidationSplitExample extends AnyRef

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  31. class JavaMultilayerPerceptronClassifierExample extends AnyRef

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  32. class JavaNGramExample extends AnyRef

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  33. class JavaNaiveBayesExample extends AnyRef

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  34. class JavaNormalizerExample extends AnyRef

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  35. class JavaOneHotEncoderExample extends AnyRef

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  36. class JavaOneVsRestExample extends AnyRef

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  37. class JavaPCAExample extends AnyRef

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  38. class JavaPipelineExample extends AnyRef

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  39. class JavaPolynomialExpansionExample extends AnyRef

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  40. class JavaQuantileDiscretizerExample extends AnyRef

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  41. class JavaRFormulaExample extends AnyRef

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  42. class JavaRandomForestClassifierExample extends AnyRef

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  43. class JavaRandomForestRegressorExample extends AnyRef

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  44. class JavaSQLTransformerExample extends AnyRef

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  45. class JavaSimpleParamsExample extends AnyRef

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  46. class JavaSimpleTextClassificationPipeline extends AnyRef

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  47. class JavaStandardScalerExample extends AnyRef

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  48. class JavaStopWordsRemoverExample extends AnyRef

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  49. class JavaStringIndexerExample extends AnyRef

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  50. class JavaTfIdfExample extends AnyRef

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  51. class JavaTokenizerExample extends AnyRef

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  52. class JavaVectorAssemblerExample extends AnyRef

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  53. class JavaVectorIndexerExample extends AnyRef

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  54. class JavaVectorSlicerExample extends AnyRef

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  55. class JavaWord2VecExample extends AnyRef

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  56. case class LabeledDocument(id: Long, text: String, label: Double) extends Product with Serializable

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    Annotations
    @BeanInfo()

Value Members

  1. object AFTSurvivalRegressionExample

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    An example demonstrating AFTSurvivalRegression.

    An example demonstrating AFTSurvivalRegression. Run with

    bin/run-example ml.AFTSurvivalRegressionExample
  2. object ALSExample

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    An example demonstrating ALS.

    An example demonstrating ALS. Run with

    bin/run-example ml.ALSExample
  3. object BinarizerExample

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  4. object BisectingKMeansExample

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    An example demonstrating bisecting k-means clustering.

    An example demonstrating bisecting k-means clustering. Run with

    bin/run-example ml.BisectingKMeansExample
  5. object BucketizerExample

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  6. object ChiSqSelectorExample

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  7. object CountVectorizerExample

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  8. object DCTExample

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  9. object DataFrameExample

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    An example of how to use org.apache.spark.sql.DataFrame for ML.

    An example of how to use org.apache.spark.sql.DataFrame for ML. Run with

    ./bin/run-example ml.DataFrameExample [options]

    If you use it as a template to create your own app, please use spark-submit to submit your app.

  10. object DecisionTreeClassificationExample

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  11. object DecisionTreeExample

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    An example runner for decision trees.

    An example runner for decision trees. Run with

    ./bin/run-example ml.DecisionTreeExample [options]

    Note that Decision Trees can take a large amount of memory. If the run-example command above fails, try running via spark-submit and specifying the amount of memory as at least 1g. For local mode, run

    ./bin/spark-submit --class org.apache.spark.examples.ml.DecisionTreeExample --driver-memory 1g
      [examples JAR path] [options]

    If you use it as a template to create your own app, please use spark-submit to submit your app.

  12. object DecisionTreeRegressionExample

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  13. object DeveloperApiExample

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    A simple example demonstrating how to write your own learning algorithm using Estimator, Transformer, and other abstractions.

    A simple example demonstrating how to write your own learning algorithm using Estimator, Transformer, and other abstractions. This mimics org.apache.spark.ml.classification.LogisticRegression. Run with

    bin/run-example ml.DeveloperApiExample
  14. object ElementwiseProductExample

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  15. object EstimatorTransformerParamExample

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  16. object GBTExample

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    An example runner for decision trees.

    An example runner for decision trees. Run with

    ./bin/run-example ml.GBTExample [options]

    Decision Trees and ensembles can take a large amount of memory. If the run-example command above fails, try running via spark-submit and specifying the amount of memory as at least 1g. For local mode, run

    ./bin/spark-submit --class org.apache.spark.examples.ml.GBTExample --driver-memory 1g
      [examples JAR path] [options]

    If you use it as a template to create your own app, please use spark-submit to submit your app.

  17. object GaussianMixtureExample

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    An example demonstrating Gaussian Mixture Model (GMM).

    An example demonstrating Gaussian Mixture Model (GMM). Run with

    bin/run-example ml.GaussianMixtureExample
  18. object GeneralizedLinearRegressionExample

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    An example demonstrating generalized linear regression.

    An example demonstrating generalized linear regression. Run with

    bin/run-example ml.GeneralizedLinearRegressionExample
  19. object GradientBoostedTreeClassifierExample

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  20. object GradientBoostedTreeRegressorExample

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  21. object IndexToStringExample

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  22. object IsotonicRegressionExample

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    An example demonstrating Isotonic Regression.

    An example demonstrating Isotonic Regression. Run with

    bin/run-example ml.IsotonicRegressionExample
  23. object KMeansExample

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    An example demonstrating k-means clustering.

    An example demonstrating k-means clustering. Run with

    bin/run-example ml.KMeansExample
  24. object LDAExample

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    An example demonstrating LDA.

    An example demonstrating LDA. Run with

    bin/run-example ml.LDAExample
  25. object LinearRegressionExample

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    An example runner for linear regression with elastic-net (mixing L1/L2) regularization.

    An example runner for linear regression with elastic-net (mixing L1/L2) regularization. Run with

    bin/run-example ml.LinearRegressionExample [options]

    A synthetic dataset can be found at data/mllib/sample_linear_regression_data.txt which can be trained by

    bin/run-example ml.LinearRegressionExample --regParam 0.15 --elasticNetParam 1.0 \
      data/mllib/sample_linear_regression_data.txt

    If you use it as a template to create your own app, please use spark-submit to submit your app.

  26. object LinearRegressionWithElasticNetExample

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  27. object LogisticRegressionExample

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    An example runner for logistic regression with elastic-net (mixing L1/L2) regularization.

    An example runner for logistic regression with elastic-net (mixing L1/L2) regularization. Run with

    bin/run-example ml.LogisticRegressionExample [options]

    A synthetic dataset can be found at data/mllib/sample_libsvm_data.txt which can be trained by

    bin/run-example ml.LogisticRegressionExample --regParam 0.3 --elasticNetParam 0.8 \
      data/mllib/sample_libsvm_data.txt

    If you use it as a template to create your own app, please use spark-submit to submit your app.

  28. object LogisticRegressionSummaryExample

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  29. object LogisticRegressionWithElasticNetExample

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  30. object MaxAbsScalerExample

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  31. object MinMaxScalerExample

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  32. object ModelSelectionViaCrossValidationExample

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    A simple example demonstrating model selection using CrossValidator.

    A simple example demonstrating model selection using CrossValidator. This example also demonstrates how Pipelines are Estimators.

    Run with

    bin/run-example ml.ModelSelectionViaCrossValidationExample
  33. object ModelSelectionViaTrainValidationSplitExample

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    A simple example demonstrating model selection using TrainValidationSplit.

    A simple example demonstrating model selection using TrainValidationSplit.

    Run with

    bin/run-example ml.ModelSelectionViaTrainValidationSplitExample
  34. object MultilayerPerceptronClassifierExample

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    An example for Multilayer Perceptron Classification.

  35. object NGramExample

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  36. object NaiveBayesExample

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  37. object NormalizerExample

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  38. object OneHotEncoderExample

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  39. object OneVsRestExample

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    An example of Multiclass to Binary Reduction with One Vs Rest, using Logistic Regression as the base classifier.

    An example of Multiclass to Binary Reduction with One Vs Rest, using Logistic Regression as the base classifier. Run with

    ./bin/run-example ml.OneVsRestExample
  40. object PCAExample

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  41. object PipelineExample

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  42. object PolynomialExpansionExample

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  43. object QuantileDiscretizerExample

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  44. object RFormulaExample

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  45. object RandomForestClassifierExample

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  46. object RandomForestExample

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    An example runner for decision trees.

    An example runner for decision trees. Run with

    ./bin/run-example ml.RandomForestExample [options]

    Decision Trees and ensembles can take a large amount of memory. If the run-example command above fails, try running via spark-submit and specifying the amount of memory as at least 1g. For local mode, run

    ./bin/spark-submit --class org.apache.spark.examples.ml.RandomForestExample --driver-memory 1g
      [examples JAR path] [options]

    If you use it as a template to create your own app, please use spark-submit to submit your app.

  47. object RandomForestRegressorExample

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  48. object SQLTransformerExample

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  49. object SimpleParamsExample

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    A simple example demonstrating ways to specify parameters for Estimators and Transformers.

    A simple example demonstrating ways to specify parameters for Estimators and Transformers. Run with

    bin/run-example ml.SimpleParamsExample
  50. object SimpleTextClassificationPipeline

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    A simple text classification pipeline that recognizes "spark" from input text.

    A simple text classification pipeline that recognizes "spark" from input text. This is to show how to create and configure an ML pipeline. Run with

    bin/run-example ml.SimpleTextClassificationPipeline
  51. object StandardScalerExample

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  52. object StopWordsRemoverExample

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  53. object StringIndexerExample

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  54. object TfIdfExample

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  55. object TokenizerExample

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  56. object UnaryTransformerExample

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    An example demonstrating creating a custom org.apache.spark.ml.Transformer using the UnaryTransformer abstraction.

    An example demonstrating creating a custom org.apache.spark.ml.Transformer using the UnaryTransformer abstraction.

    Run with

    bin/run-example ml.UnaryTransformerExample
  57. object VectorAssemblerExample

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  58. object VectorIndexerExample

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  59. object VectorSlicerExample

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  60. object Word2VecExample

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Ungrouped