Serialized Form

Package hex.genmodel

Class hex.genmodel.GenModel extends java.lang.Object implements Serializable

Serialized Fields

_names

java.lang.String[] _names

Column names; last is response for supervised models

_domains

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.

Class hex.genmodel.GenMunger extends java.lang.Object implements Serializable

Serialized Fields

_steps

GenMunger.Step<T>[] _steps

Class hex.genmodel.GenMunger.Step extends java.lang.Object implements Serializable

Serialized Fields

_names

java.lang.String[] _names

_types

java.lang.String[] _types

_outNames

java.lang.String[] _outNames

_params

java.util.HashMap<K,V> _params

Package hex.genmodel.easy

Class hex.genmodel.easy.EasyPredictModelWrapper extends java.lang.Object implements Serializable

Serialized Fields

m

GenModel m

modelColumnNameToIndexMap

java.util.HashMap<K,V> modelColumnNameToIndexMap

domainMap

java.util.HashMap<K,V> domainMap

Class hex.genmodel.easy.RowData extends java.util.HashMap<java.lang.String,java.lang.Object> implements Serializable

Package hex.genmodel.easy.exception

Class hex.genmodel.easy.exception.PredictException extends java.lang.Exception implements Serializable

Class hex.genmodel.easy.exception.PredictUnknownCategoricalLevelException extends PredictException implements Serializable

Serialized Fields

columnName

java.lang.String columnName

unknownLevel

java.lang.String unknownLevel

Class hex.genmodel.easy.exception.PredictUnknownTypeException extends PredictException implements Serializable

Class hex.genmodel.easy.exception.PredictWrongModelCategoryException extends PredictException implements Serializable

Package hex.genmodel.easy.prediction

Class hex.genmodel.easy.prediction.AbstractPrediction extends java.lang.Object implements Serializable

Class hex.genmodel.easy.prediction.AutoEncoderModelPrediction extends AbstractPrediction implements Serializable

Class hex.genmodel.easy.prediction.BinomialModelPrediction extends AbstractPrediction implements Serializable

Serialized Fields

labelIndex

int labelIndex

0 or 1.

label

java.lang.String label

Label of the predicted level.

classProbabilities

double[] classProbabilities

This array of length two has the class probability for each class (aka categorical or factor level) in the response column. The array corresponds to the level names returned by:

 model.getDomainValues(model.getResponseIdx())
 

"Domain" is the internal H2O term for level names. The values in this array may be Double.NaN, which means NA (this will happen with GLM, for example, if one of the input values for a new data point is NA). If they are valid numeric values, then they will sum up to 1.0.

Class hex.genmodel.easy.prediction.ClusteringModelPrediction extends AbstractPrediction implements Serializable

Serialized Fields

cluster

int cluster

Chosen cluster for this data point.

Class hex.genmodel.easy.prediction.MultinomialModelPrediction extends AbstractPrediction implements Serializable

Serialized Fields

labelIndex

int labelIndex

Index number of the predicted class (aka categorical or factor level) in the response column.

label

java.lang.String label

Label of the predicted level.

classProbabilities

double[] classProbabilities

This array has an element for each class (aka categorical or factor level) in the response column. The array corresponds to the level names returned by:

 model.getDomainValues(model.getResponseIdx())
 

"Domain" is the internal H2O term for level names. The values in this array may be Double.NaN, which means NA. If they are valid numeric values, then they will sum up to 1.0.

Class hex.genmodel.easy.prediction.RegressionModelPrediction extends AbstractPrediction implements Serializable

Serialized Fields

value

double value

This value may be Double.NaN, which means NA (this will happen with GLM, for example, if one of the input values for a new data point is NA).