ml - snappy-spark-examples_2.10 1.6.0-BETA API - org.apache.spark.examples.ml

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

Annotations
@BeanInfo()
class JavaCountVectorizerExample extends AnyRef
class JavaCrossValidatorExample extends AnyRef
class JavaDeveloperApiExample extends AnyRef
class JavaKMeansExample extends AnyRef
class JavaOneVsRestExample extends AnyRef
class JavaSimpleParamsExample extends AnyRef
class JavaSimpleTextClassificationPipeline extends AnyRef
class JavaTfIdfExample extends AnyRef
class JavaTrainValidationSplitExample extends AnyRef
class JavaWord2VecExample extends AnyRef
case class LabeledDocument(id: Long, text: String, label: Double) extends Product with Serializable

Annotations
@BeanInfo()

object CountVectorizerExample
object CrossValidatorExample

A simple example demonstrating model selection using CrossValidator.
object DecisionTreeExample

An example runner for decision trees.
object DeveloperApiExample

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

An example runner for decision trees.
object KMeansExample

An example demonstrating a k-means clustering.
object LinearRegressionExample

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

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

An example app for ALS on MovieLens data (http://grouplens.
object OneVsRestExample

An example runner for Multiclass to Binary Reduction with One Vs Rest.
object RandomForestExample

An example runner for decision trees.
object SimpleParamsExample

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

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

A simple example demonstrating model selection using TrainValidationSplit.
object Word2VecExample

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