Class SmileClassifier

java.lang.Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Estimator<SmileClassificationModel>
org.apache.spark.ml.Predictor<org.apache.spark.ml.linalg.Vector, SmileClassifier, SmileClassificationModel>
org.apache.spark.ml.classification.Classifier<org.apache.spark.ml.linalg.Vector, SmileClassifier, SmileClassificationModel>
smile.spark.SmileClassifier
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, org.apache.spark.ml.classification.ClassifierParams, org.apache.spark.ml.param.Params, org.apache.spark.ml.param.shared.HasFeaturesCol, org.apache.spark.ml.param.shared.HasLabelCol, org.apache.spark.ml.param.shared.HasPredictionCol, org.apache.spark.ml.param.shared.HasRawPredictionCol, org.apache.spark.ml.PredictorParams, org.apache.spark.ml.util.Identifiable, org.apache.spark.ml.util.MLWritable
public class SmileClassifier extends org.apache.spark.ml.classification.Classifier<org.apache.spark.ml.linalg.Vector, SmileClassifier, SmileClassificationModel> implements org.apache.spark.ml.util.MLWritable
A Spark ML Estimator that trains a SMILE classification model.
See Also:

  • Nested Class Summary

    Nested Classes
    Modifier and Type
    Class
    Description
    static interface 
    SmileClassifier.Trainer
    Functional interface for training a SMILE classifier on double feature arrays.

    Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

    org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

  • Constructor Summary

    Constructors
    Constructor
    Description
    SmileClassifier()
    Default constructor with a random UID.
    SmileClassifier(String uid)
    Constructor with a custom UID.

  • Method Summary

    Modifier and Type
    Method
    Description
    SmileClassifier
    copy(org.apache.spark.ml.param.ParamMap extra)
     
    int
    getNumClasses()
    Returns the configured number of classes, or -1 if auto-detected.
    SmileClassifier.Trainer
    getTrainer()
    Returns the trainer function.
    static SmileClassifier
    load(String path)
    Loads a persisted SmileClassifier from the given path.
    static org.apache.spark.ml.util.MLReader<SmileClassifier>
    read()
    Returns an MLReader instance to load a persisted SmileClassifier.
    SmileClassifier
    setNumClasses(int numClasses)
    Sets the number of classes explicitly.
    SmileClassifier
    setTrainer(SmileClassifier.Trainer trainer)
    Sets the trainer function.
    SmileClassificationModel
    train(org.apache.spark.sql.Dataset<?> dataset)
     
    String
    uid()
     
    org.apache.spark.ml.util.MLWriter
    write()
     

    Methods inherited from class org.apache.spark.ml.classification.Classifier

    getNumClasses, getNumClasses$default$2, getRawPredictionCol, org$apache$spark$ml$param$shared$HasRawPredictionCol$_setter_$rawPredictionCol_$eq, rawPredictionCol, setRawPredictionCol, validateAndTransformSchema

    Methods inherited from class org.apache.spark.ml.Predictor

    featuresCol, featuresDataType, fit, getFeaturesCol, getLabelCol, getPredictionCol, labelCol, org$apache$spark$ml$param$shared$HasFeaturesCol$_setter_$featuresCol_$eq, org$apache$spark$ml$param$shared$HasLabelCol$_setter_$labelCol_$eq, org$apache$spark$ml$param$shared$HasPredictionCol$_setter_$predictionCol_$eq, predictionCol, setFeaturesCol, setLabelCol, setPredictionCol, transformSchema

    Methods inherited from class org.apache.spark.ml.Estimator

    estimateModelSize, fit, fit, fit, fit

    Methods inherited from class org.apache.spark.ml.PipelineStage

    $, clear, copyValues, copyValues$default$2, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isDefined, isSet, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, onParamChange, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$ml$param$Params$_setter_$defaultParamMap_$eq, org$apache$spark$ml$param$Params$_setter_$paramMap_$eq, paramMap, params, set, set, set, setDefault, setDefault, toString, transformSchema, withLogContext

    Methods inherited from class Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

    Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

    featuresCol, getFeaturesCol, org$apache$spark$ml$param$shared$HasFeaturesCol$_setter_$featuresCol_$eq

    Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

    getLabelCol, labelCol, org$apache$spark$ml$param$shared$HasLabelCol$_setter_$labelCol_$eq

    Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

    getPredictionCol, org$apache$spark$ml$param$shared$HasPredictionCol$_setter_$predictionCol_$eq, predictionCol

    Methods inherited from interface org.apache.spark.ml.util.Identifiable

    toString

    Methods inherited from interface org.apache.spark.ml.util.MLWritable

    save

    Methods inherited from interface org.apache.spark.ml.param.Params

    $, clear, copyValues, copyValues$default$2, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, org$apache$spark$ml$param$Params$_setter_$defaultParamMap_$eq, org$apache$spark$ml$param$Params$_setter_$paramMap_$eq, paramMap, params, set, set, set, setDefault, setDefault

  • Constructor Details

    • SmileClassifier

      public SmileClassifier()
      Default constructor with a random UID.

    • SmileClassifier

      public SmileClassifier(String uid)
      Constructor with a custom UID.
      Parameters:
      uid - the instance UID.

  • Method Details

    • uid

      public String uid()
      Specified by:
      uid in interface org.apache.spark.ml.util.Identifiable

    • getTrainer

      public SmileClassifier.Trainer getTrainer()
      Returns the trainer function.
      Returns:
      the trainer function.

    • setTrainer

      public SmileClassifier setTrainer(SmileClassifier.Trainer trainer)
      Sets the trainer function.
      Parameters:
      trainer - the trainer function.
      Returns:
      this estimator.

    • getNumClasses

      public int getNumClasses()
      Returns the configured number of classes, or -1 if auto-detected.
      Returns:
      the number of classes.

    • setNumClasses

      public SmileClassifier setNumClasses(int numClasses)
      Sets the number of classes explicitly.
      Parameters:
      numClasses - the number of classes.
      Returns:
      this estimator.

    • copy

      public SmileClassifier copy(org.apache.spark.ml.param.ParamMap extra)
      Specified by:
      copy in interface org.apache.spark.ml.param.Params
      Specified by:
      copy in class org.apache.spark.ml.Predictor<org.apache.spark.ml.linalg.Vector, SmileClassifier, SmileClassificationModel>

    • train

      public SmileClassificationModel train(org.apache.spark.sql.Dataset<?> dataset)
      Specified by:
      train in class org.apache.spark.ml.Predictor<org.apache.spark.ml.linalg.Vector, SmileClassifier, SmileClassificationModel>

    • write

      public org.apache.spark.ml.util.MLWriter write()
      Specified by:
      write in interface org.apache.spark.ml.util.MLWritable

    • read

      public static org.apache.spark.ml.util.MLReader<SmileClassifier> read()
      Returns an MLReader instance to load a persisted SmileClassifier.
      Returns:
      the reader.

    • load

      public static SmileClassifier load(String path)
      Loads a persisted SmileClassifier from the given path.
      Parameters:
      path - the path.
      Returns:
      the loaded estimator.