hex.nn

Class NNModel

java.lang.Object

water.Iced

water.Lockable<Model>

water.Model

hex.nn.NNModel

All Implemented Interfaces:

java.lang.Cloneable, Freezable

public class NNModel
extends Model

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	NNModel.Errors
static class	NNModel.NNModelInfo

Field Summary

Fields

Modifier and Type	Field and Description
static DocGen.FieldDoc[]	DOC_FIELDS
double	epoch_counter
NNModel.Errors[]	errors

Fields inherited from class water.Model

_dataKey, _domains, _names

Fields inherited from class water.Lockable

_key, _lockers

Constructor Summary

Constructors

Constructor and Description
NNModel(Key selfKey, Key jobKey, Key dataKey, FrameTask.DataInfo dinfo, NN params)

Method Summary

Methods

Modifier and Type	Method and Description
double	calcError(Frame ftest, java.lang.String label, boolean printCM, ConfusionMatrix CM)
ConfusionMatrix	cm() for grid search error reporting
void	delete()
boolean	generateHTML(java.lang.String title, java.lang.StringBuilder sb)
NNModel.NNModelInfo	model_info()
float[]	score0(double[] data, float[] preds) Subclasses implement the scoring logic.
java.lang.String	toJava() Return a String which is a valid Java program representing a class that implements the Model.
boolean	toJavaHtml(java.lang.StringBuilder sb)
java.lang.String	toString()

Methods inherited from class water.Model

adapt, classNames, delete_impl, errStr, getDomainMapping, getDomainMapping, getPrediction, getPrediction, isClassifier, mse, nclasses, responseName, score, score, score, score, score, score0, testJavaScoring, toJava, toJavaDefaultMaxIters, toJavaInit, toJavaInit, toJavaPredictBody, toJavaSuper, varimp

Methods inherited from class water.Lockable

delete_and_lock, delete, delete, delete, read_lock, read_lock, unlock, update, write_lock

Methods inherited from class water.Iced

clone, frozenType, init, newInstance, read, toDocField, write, writeJSON, writeJSONFields

Methods inherited from class java.lang.Object

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

Field Detail

DOC_FIELDS

public static DocGen.FieldDoc[] DOC_FIELDS

epoch_counter

public double epoch_counter

errors

public NNModel.Errors[] errors

Constructor Detail

NNModel

public NNModel(Key selfKey,
       Key jobKey,
       Key dataKey,
       FrameTask.DataInfo dinfo,
       NN params)

Method Detail

model_info

public final NNModel.NNModelInfo model_info()

delete

public void delete()

Overrides:

delete in class Lockable<Model>

cm

public ConfusionMatrix cm()

for grid search error reporting

Overrides:

cm in class Model

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

score0

public float[] score0(double[] data,
             float[] preds)

Description copied from class: Model

Subclasses implement the scoring logic. The data is pre-loaded into a re-used temp array, in the order the model expects. The predictions are loaded into the re-used temp array, which is also returned.

Specified by:

score0 in class Model

calcError

public double calcError(Frame ftest,
               java.lang.String label,
               boolean printCM,
               ConfusionMatrix CM)

generateHTML

public boolean generateHTML(java.lang.String title,
                   java.lang.StringBuilder sb)

toJavaHtml

public boolean toJavaHtml(java.lang.StringBuilder sb)

toJava

public java.lang.String toJava()

Description copied from class: Model

Return a String which is a valid Java program representing a class that implements the Model. The Java is of the form:

    class UUIDxxxxModel {
      public static final String NAMES[] = { ....column names... }
      public static final String DOMAINS[][] = { ....domain names... }
      // Pass in data in a double[], pre-aligned to the Model's requirements.
      // Jam predictions into the preds[] array; preds[0] is reserved for the
      // main prediction (class for classifiers or value for regression),
      // and remaining columns hold a probability distribution for classifiers.
      float[] predict( double data[], float preds[] );
      double[] map( HashMap row, double data[] );
      // Does the mapping lookup for every row, no allocation
      float[] predict( HashMap row, double data[], float preds[] );
      // Allocates a double[] for every row
      float[] predict( HashMap row, float preds[] );
      // Allocates a double[] and a float[] for every row
      float[] predict( HashMap row );
    }
  

Overrides:

toJava in class Model