RegressionModel
The regression functions are used to determine the relationship between the dependent variable (target field) and one or more independent variables. The dependent variable is the one whose values you want to predict, whereas the independent variables are the variables that you base your prediction on. While the term regression usually refers to the prediction of numeric values, the PMML element RegressionModel can also be used for classification. This is due to the fact that multiple regression equations can be combined in order to predict categorical values.
Value members
Concrete methods
Creates an object of RegressionOutputs that is for writing into an output series.
Creates an object of RegressionOutputs that is for writing into an output series.
- Definition Classes
Returns all candidates output fields of this model when there is no output specified explicitly.
Returns all candidates output fields of this model when there is no output specified explicitly.
- Definition Classes
Predicts values for a given data series.
Predicts values for a given data series.
- Definition Classes
- Model -> Predictable
Inherited methods
Returns class labels of the specified target.
Returns class labels of the specified target.
- Inherited from:
- Model
Returns PMML version as a double value
Returns PMML version as a double value
- Inherited from:
- HasVersion
Returns the field of a given name.
Returns the field of a given name.
- Throws:
- FieldNotFoundException
if a field with the given name does not exist
- Inherited from:
- HasField
Get fields by its usage type: 'active', 'target', 'predicted', 'group' and so on
Get fields by its usage type: 'active', 'target', 'predicted', 'group' and so on
- Inherited from:
- Model
Tests if this is a association rules model.
Tests if this is a association rules model.
- Inherited from:
- HasModelAttributes
Tests if this is a classification model.
Tests if this is a classification model.
- Definition Classes
- Inherited from:
- Model
Tests if this is a classification model of the specified target, it's applicable for multiple targets.
Tests if this is a classification model of the specified target, it's applicable for multiple targets.
- Inherited from:
- Model
Tests if this is a clustering model.
Tests if this is a clustering model.
- Inherited from:
- HasModelAttributes
Tests if the target is an ordinal field
Tests if the target is an ordinal field
- Inherited from:
- Model
Tests if this is a regression model.
Tests if this is a regression model.
- Definition Classes
- Inherited from:
- Model
Tests if this is a regression model of the specified target, it's applicable for multiple targets.
Tests if this is a regression model of the specified target, it's applicable for multiple targets.
- Inherited from:
- Model
Tests if this is a sequences model.
Tests if this is a sequences model.
- Inherited from:
- HasModelAttributes
Tests if this is a time series model.
Tests if this is a time series model.
- Inherited from:
- HasModelAttributes
Returns the number of class labels of the specified target.
Returns the number of class labels of the specified target.
- Inherited from:
- Model
Returns optype of the specified target.
Returns optype of the specified target.
- Inherited from:
- Model
Predicts one or multiple records in json format, there are two formats supported:
Predicts one or multiple records in json format, there are two formats supported:
- ‘records’ : list like [{column -> value}, … , {column -> value}]
- ‘split’ : dict like {‘columns’ -> [columns], ‘data’ -> [values]}
- Value parameters:
- json
Records in json
- Returns:
Results in json
- Inherited from:
- Model
Predicts values for a given Array, and the order of those values is supposed as same as the input fields list
Predicts values for a given Array, and the order of those values is supposed as same as the input fields list
- Inherited from:
- Model
Predicts values for a given list of key/value pairs.
Predicts values for a given list of key/value pairs.
- Inherited from:
- Model
Predicts values for a given data map of Java.
Predicts values for a given data map of Java.
- Inherited from:
- Model
Tests if probabilities of categories of target can be produced by this model.
Tests if probabilities of categories of target can be produced by this model.
- Inherited from:
- Model
Returns targets that are residual values to be computed, the input data must include target values.
Returns targets that are residual values to be computed, the input data must include target values.
- Inherited from:
- HasOutput
Name of the first target for the supervised model.
Name of the first target for the supervised model.
- Inherited from:
- HasTargetFields
The optional transformation dictionary.
The optional transformation dictionary.
- Inherited from:
- Model
Concrete fields
Inherited fields
The class labels in a classification model.
The class labels in a classification model.
- Inherited from:
- Model
User-defined custom output fields, both the internal output of PMML and predefined output are ignored when the field is specified.
User-defined custom output fields, both the internal output of PMML and predefined output are ignored when the field is specified.
- Inherited from:
- HasOutput
Implicit referenced derived fields for the sub-model except ones defined in the mining schema.
Implicit referenced derived fields for the sub-model except ones defined in the mining schema.
- Inherited from:
- Model
A series with all null values is returned when can not produce a result.
A series with all null values is returned when can not produce a result.
- Inherited from:
- Model
The number of class labels in a classification model.
The number of class labels in a classification model.
- Inherited from:
- Model
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists. If the target does not specify optype then the MiningField is used as default. And, in turn, if the MiningField does not specify an optype, it is taken from the corresponding DataField. In other words, a MiningField overrides a DataField, and a Target overrides a MiningField.
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists. If the target does not specify optype then the MiningField is used as default. And, in turn, if the MiningField does not specify an optype, it is taken from the corresponding DataField. In other words, a MiningField overrides a DataField, and a Target overrides a MiningField.
- Inherited from:
- Model
A flag for whether to return those predefined output fields not exist in the output element explicitly.
A flag for whether to return those predefined output fields not exist in the output element explicitly.
- Inherited from:
- HasOutput
The class labels of all categorical targets.
The class labels of all categorical targets.
- Inherited from:
- Model
The first target field for the supervised model.
The first target field for the supervised model.
- Inherited from:
- Model
All target fields in an array. Multiple target fields are allowed. It depends on the kind of the model whether prediction of multiple fields is supported.
All target fields in an array. Multiple target fields are allowed. It depends on the kind of the model whether prediction of multiple fields is supported.
- Inherited from:
- Model
Setup indices to retrieve data from series faster by index instead of name, the index is immutable when model is built because the model object could run in multiple threads, so it's important make sure the model object is totally immutable.
Setup indices to retrieve data from series faster by index instead of name, the index is immutable when model is built because the model object could run in multiple threads, so it's important make sure the model object is totally immutable.
Setup indices of targets that are usually not used by the scoring process, they are only used when residual values to be computed.
- Inherited from:
- Model