Model.Output (h2o-core 3.0.0 API)

java.lang.Object
- water.Iced
- - hex.Model.Output

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, Freezable

Direct Known Subclasses:

ClusteringModel.ClusteringOutput, QuantileModel.QuantileOutput

Enclosing class:

Model<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output>
```
public abstract static class Model.Output
extends Iced
```
Model-specific output class. Each model sub-class contains an instance of one of these containing its "output": the pieces of the model needed for scoring. E.g. KMeansModel has a KMeansOutput extending Model.Output which contains the cluster centers. The output also includes the names, domains and other fields which are determined at training time.

See Also:
Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`long[]`	`_distribution`
`java.lang.String[][]`	`_domains` Categorical/factor/enum mappings, per column.
`protected boolean`	`_hasOffset` The name of the response column (which is always the last column).
`protected boolean`	`_hasWeights`
`protected boolean`	`_isSupervised`
`Key[]`	`_model_metrics` List of all the associated ModelMetrics objects, so we can delete them when we delete this model.
`TwoDimTable`	`_model_summary` User-facing model summary - Display model type, complexity, size and other useful stats
`double[]`	`_modelClassDist`
`java.lang.String[]`	`_names` Columns used in the model and are used to match up with scoring data columns.
`double[]`	`_priorClassDist`
`TwoDimTable`	`_scoring_history` User-facing model scoring history - 2D table with modeling accuracy as a function of time/trees/epochs/iterations, etc.
`Job.JobState`	`_state` Job state (CANCELLED, FAILED, DONE).
`ModelMetrics`	`_training_metrics` Training set metrics obtained during model training
`ModelMetrics`	`_validation_metrics` Validation set metrics obtained during model training (if a validation data set was specified)

Constructor Summary

Constructors
Constructor and Description
`Model.Output()`
`Model.Output(boolean hasWeights, boolean hasOffset)`
`Model.Output(ModelBuilder b)` Any final prep-work just before model-building starts, but after the user has clicked "go".

Method Summary

Methods
Modifier and Type	Method and Description
`ModelMetrics`	`addModelMetrics(ModelMetrics mm)`
`java.lang.String[]`	`classNames()` The names of the levels for an enum (categorical) response column.
`hex.ModelCategory`	`getModelCategory()`
`boolean`	`hasOffset()`
`boolean`	`hasWeights()`
`boolean`	`isClassifier()` Is this model a classification model? (v.
`boolean`	`isSupervised()`
`int`	`nclasses()`
`int`	`nfeatures()` Returns number of input features (OK for most unsupervised methods, need to override for supervised!)
`int`	`offsetIdx()`
`java.lang.String`	`offsetName()`
`int`	`responseIdx()`
`java.lang.String`	`responseName()`
`java.lang.String`	`toString()`
`int`	`weightsIdx()`
`java.lang.String`	`weightsName()`

Methods inherited from class water.Iced
clone, frozenType, read_impl, read, readExternal, readJSON_impl, readJSON, toJsonString, write_impl, write, writeExternal, writeHTML_impl, writeHTML, writeJSON_impl, writeJSON

Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - _names
```
public java.lang.String[] _names
```
    Columns used in the model and are used to match up with scoring data columns. The last name is the response column name (if any).
  - _domains
```
public java.lang.String[][] _domains
```
    Categorical/factor/enum mappings, per column. Null for non-enum cols. Columns match the post-init cleanup columns. The last column holds the response col enums for SupervisedModels.
  - _model_metrics
```
public Key[] _model_metrics
```
    List of all the associated ModelMetrics objects, so we can delete them when we delete this model.
  - _state
```
public Job.JobState _state
```
    Job state (CANCELLED, FAILED, DONE). TODO: Really the whole Job (run-time, etc) but that has to wait until Job is split from ModelBuilder.
  - _training_metrics
```
public ModelMetrics _training_metrics
```
    Training set metrics obtained during model training
  - _validation_metrics
```
public ModelMetrics _validation_metrics
```
    Validation set metrics obtained during model training (if a validation data set was specified)
  - _model_summary
```
public TwoDimTable _model_summary
```
    User-facing model summary - Display model type, complexity, size and other useful stats
  - _scoring_history
```
public TwoDimTable _scoring_history
```
    User-facing model scoring history - 2D table with modeling accuracy as a function of time/trees/epochs/iterations, etc.
  - _isSupervised
```
protected boolean _isSupervised
```
  - _hasOffset
```
protected final boolean _hasOffset
```
    The name of the response column (which is always the last column).
  - _hasWeights
```
protected final boolean _hasWeights
```
  - _distribution
```
public long[] _distribution
```
  - _modelClassDist
```
public double[] _modelClassDist
```
  - _priorClassDist
```
public double[] _priorClassDist
```
- Constructor Detail
  - Model.Output
```
public Model.Output()
```
  - Model.Output
```
public Model.Output(boolean hasWeights,
            boolean hasOffset)
```
  - Model.Output
```
public Model.Output(ModelBuilder b)
```
    Any final prep-work just before model-building starts, but after the user has clicked "go". E.g., converting a response column to an enum touches the entire column (can be expensive), makes a parallel vec (Key/Data leak management issues), and might throw IAE if there are too many classes.
- Method Detail
  - nfeatures
```
public int nfeatures()
```
    Returns number of input features (OK for most unsupervised methods, need to override for supervised!)
  - isSupervised
```
public boolean isSupervised()
```
  - hasOffset
```
public boolean hasOffset()
```
  - hasWeights
```
public boolean hasWeights()
```
  - responseName
```
public java.lang.String responseName()
```
  - weightsName
```
public java.lang.String weightsName()
```
  - offsetName
```
public java.lang.String offsetName()
```
  - responseIdx
```
public int responseIdx()
```
  - weightsIdx
```
public int weightsIdx()
```
  - offsetIdx
```
public int offsetIdx()
```
  - classNames
```
public java.lang.String[] classNames()
```
    The names of the levels for an enum (categorical) response column.
  - isClassifier
```
public boolean isClassifier()
```
    Is this model a classification model? (v. a regression or clustering model)
  - nclasses
```
public int nclasses()
```
  - getModelCategory
```
public hex.ModelCategory getModelCategory()
```
  - addModelMetrics
```
public ModelMetrics addModelMetrics(ModelMetrics mm)
```
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object

Class Model.Output

Field Summary

Constructor Summary

Method Summary

Methods inherited from class water.Iced

Methods inherited from class java.lang.Object

Field Detail

_names

_domains

_model_metrics

_state

_training_metrics

_validation_metrics

_model_summary

_scoring_history

_isSupervised

_hasOffset

_hasWeights

_distribution

_modelClassDist

_priorClassDist

Constructor Detail

Model.Output

Model.Output

Model.Output

Method Detail

nfeatures

isSupervised

hasOffset

hasWeights

responseName

weightsName

offsetName

responseIdx

weightsIdx

offsetIdx

classNames

isClassifier

nclasses

getModelCategory

addModelMetrics

toString