Record Class VectorQuantizerModel

java.lang.Object
java.lang.Record
smile.model.VectorQuantizerModel
Record Components:
algorithm - the algorithm name.
schema - the schema of input data (without response variable).
formula - the model formula.
quantizer - the vector quantizer model.
transform - the optional feature transformation applied before quantization.
tags - the model metadata tags.
All Implemented Interfaces:
Serializable, Model
public record VectorQuantizerModel(String algorithm, StructType schema, Formula formula, VectorQuantizer quantizer, Transform transform, Properties tags) extends Record implements Model, Serializable
The vector quantization model.
See Also:

  • Constructor Details

    • VectorQuantizerModel

      public VectorQuantizerModel(String algorithm, StructType schema, Formula formula, VectorQuantizer quantizer, Transform transform, Properties tags)
      Creates an instance of a VectorQuantizerModel record class.
      Parameters:
      algorithm - the value for the algorithm record component
      schema - the value for the schema record component
      formula - the value for the formula record component
      quantizer - the value for the quantizer record component
      transform - the value for the transform record component
      tags - the value for the tags record component

  • Method Details

    • quantize

      public double[] quantize(Tuple x)
      Quantizes an input tuple to its nearest prototype/code vector.
      Parameters:
      x - the input tuple.
      Returns:
      the quantized code vector.

    • quantize

      public double[][] quantize(DataFrame data)
      Quantizes a data frame of observations.
      Parameters:
      data - the input data frame.
      Returns:
      the quantized code vectors.

    • isOnline

      public boolean isOnline()
      Description copied from interface: Model
      Returns true if this model supports online learning updates.
      Specified by:
      isOnline in interface Model
      Returns:
      true if online learning is supported.

    • update

      public void update(Tuple x)
      Description copied from interface: Model
      Online updates the model with a single observation.
      Specified by:
      update in interface Model
      Parameters:
      x - the input tuple (including target variable if supervised).

    • update

      public void update(DataFrame data)
      Description copied from interface: Model
      Online updates the model sequentially with a data frame of observations.
      Specified by:
      update in interface Model
      Parameters:
      data - the input data frame.

    • infer

      public Prediction infer(Tuple x, boolean probability, boolean explain)
      Description copied from interface: Model
      Performs inference on a single tuple.
      Specified by:
      infer in interface Model
      Parameters:
      x - the input tuple.
      probability - true to compute posterior probabilities for soft classifiers.
      explain - true to compute feature explanations.
      Returns:
      the prediction.

    • infer

      public Prediction infer(Tuple x, boolean probability, boolean explain, KernelSHAP.Options options)
      Description copied from interface: Model
      Performs inference on a single tuple with custom KernelSHAP.Options.
      Specified by:
      infer in interface Model
      Parameters:
      x - the input tuple.
      probability - true to compute posterior probabilities for soft classifiers.
      explain - true to compute feature explanations.
      options - optional KernelSHAP options (may be null).
      Returns:
      the prediction.

    • infer

      public Prediction[] infer(DataFrame data, boolean probability, boolean explain)
      Description copied from interface: Model
      Performs batch inference over a data frame.
      Specified by:
      infer in interface Model
      Parameters:
      data - the input data frame.
      probability - true to compute posterior probabilities for soft classifiers.
      explain - true to compute feature explanations.
      Returns:
      an array of predictions.

    • infer

      public Prediction[] infer(DataFrame data, boolean probability, boolean explain, KernelSHAP.Options options)
      Description copied from interface: Model
      Performs batch inference over a data frame with custom KernelSHAP.Options.
      Specified by:
      infer in interface Model
      Parameters:
      data - the input data frame.
      probability - true to compute posterior probabilities for soft classifiers.
      explain - true to compute feature explanations.
      options - optional KernelSHAP options (may be null).
      Returns:
      an array of predictions.

    • toString

      public final String toString()
      Returns a string representation of this record class. The representation contains the name of the class, followed by the name and value of each of the record components.
      Specified by:
      toString in class Record
      Returns:
      a string representation of this object

    • hashCode

      public final int hashCode()
      Returns a hash code value for this object. The value is derived from the hash code of each of the record components.
      Specified by:
      hashCode in class Record
      Returns:
      a hash code value for this object

    • equals

      public final boolean equals(Object o)
      Indicates whether some other object is "equal to" this one. The objects are equal if the other object is of the same class and if all the record components are equal. All components in this record class are compared with Objects::equals(Object,Object).
      Specified by:
      equals in class Record
      Parameters:
      o - the object with which to compare
      Returns:
      true if this object is the same as the o argument; false otherwise.

    • algorithm

      public String algorithm()
      Returns the value of the algorithm record component.
      Specified by:
      algorithm in interface Model
      Returns:
      the value of the algorithm record component

    • schema

      public StructType schema()
      Returns the value of the schema record component.
      Specified by:
      schema in interface Model
      Returns:
      the value of the schema record component

    • formula

      public Formula formula()
      Returns the value of the formula record component.
      Specified by:
      formula in interface Model
      Returns:
      the value of the formula record component

    • quantizer

      public VectorQuantizer quantizer()
      Returns the value of the quantizer record component.
      Returns:
      the value of the quantizer record component

    • transform

      public Transform transform()
      Returns the value of the transform record component.
      Returns:
      the value of the transform record component

    • tags

      public Properties tags()
      Returns the value of the tags record component.
      Specified by:
      tags in interface Model
      Returns:
      the value of the tags record component