magpie.models.regression

Class WekaRegression

java.lang.Object

magpie.models.BaseModel

magpie.models.regression.BaseRegression

magpie.models.regression.WekaRegression

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, WekaModel, AbstractRegressionModel, Citable, Commandable, Options, Printable, Savable

public class WekaRegression
extends BaseRegression
implements WekaModel

Implementation of WekaModel for regression purposes. To use this class, simply provide the name of the Weka algorithm and a list of options as input.

Example: model = new models.classification.WekaClassifier trees.REPTree -L 5

Usage: <Weka classifier> [<classifier options...>]
Weka classifier: Name of a Weka classifier model (i.e. trees.REPTree). "?" to list options
classifier options: Any options for that model. (see Weka Javadoc for these options)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
weka.classifiers.AbstractClassifier	Model Link to Weka-based model
boolean	model_defined Whether model type has been defined
protected java.lang.String[]	Model_Options Options supplied when instantiating Model
protected java.lang.String	Model_Type Name of model type currently in use

Fields inherited from class magpie.models.BaseModel

AttributeSelector, trained, TrainingStats, validated, ValidationStats

Constructor Summary

Constructors

Constructor and Description
WekaRegression() Create a WekaRegression model based on the "rules.ZeroR" algorithm
WekaRegression(java.lang.String model_type, java.lang.String[] options) Create a Weka model with a specified model and options

Method Summary

Modifier and Type	Method and Description
WekaRegression	clone()
java.util.List<org.apache.commons.lang3.tuple.Pair<java.lang.String,Citation>>	getCitations() Return a list of citations for this object and any underlying objects.
java.lang.String	getModelFull() Return model name and options
java.lang.String	getModelName() Return the model name
java.lang.String[]	getModelOptions() Return the model options
int	getNFittingParameters() Number of fitting parameters in a model.
protected java.lang.String	printModel_protected() Internal method that handles printing the model as a string.
java.util.List<java.lang.String>	printModelDescriptionDetails(boolean htmlFormat) Print details of the model.
java.lang.String	printUsage() Print out required format for options.
void	run_protected(Dataset TestData) Run a model without checking if stuff is trained (use carefully)
void	setModel(java.lang.String model_type, java.lang.String[] options) Set the underlying Weka-based model
void	setOptions(java.util.List OptionsObj) Set any options for this object.
java.lang.String	toString()
protected void	train_protected(Dataset TrainingData) Train a model without evaluating performance

Methods inherited from class magpie.models.regression.BaseRegression

doRobustRegression, getRobustRegressionQ, robustTraining, runCommand, setRobustRegressionQ

Methods inherited from class magpie.models.BaseModel

about, crossValidate, crossValidate, crossValidate, done, externallyValidate, getAttributeSelector, getFilter, getTrainTime, getValidationMethod, handleSetCommand, isTrained, isValidated, loadState, printCommand, printDescription, printModel, resetModel, run, saveCommand, saveState, setAttributeSelector, setComponent, setFilter, train, train

Methods inherited from class java.lang.Object

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

Field Detail

Model

public weka.classifiers.AbstractClassifier Model

Link to Weka-based model

model_defined

public boolean model_defined

Whether model type has been defined

Model_Type

protected java.lang.String Model_Type

Name of model type currently in use

Model_Options

protected java.lang.String[] Model_Options

Options supplied when instantiating Model

Constructor Detail

WekaRegression

public WekaRegression(java.lang.String model_type,
                      java.lang.String[] options)
               throws java.lang.Exception

Create a Weka model with a specified model and options

Parameters:

model_type - Model type (ie trees.J48)

options - Options for the model

Throws:

java.lang.Exception

WekaRegression

public WekaRegression()
               throws java.lang.Exception

Create a WekaRegression model based on the "rules.ZeroR" algorithm

Throws:

java.lang.Exception

Method Detail

setOptions

public void setOptions(java.util.List OptionsObj)
                throws java.lang.Exception

Description copied from interface: Options

Set any options for this object. If parsing the options fails, return an Exception with the usage as its message.

Specified by:

setOptions in interface Options

Parameters:

OptionsObj - Array of options as Objects - can be null

Throws:

java.lang.Exception - if problem with inputs

printUsage

public java.lang.String printUsage()

Description copied from interface: Options

Print out required format for options. For consistency, should start with "Usage: ".

Specified by:

printUsage in interface Options

Returns:

Usage for this function

clone

public WekaRegression clone()

Overrides:

clone in class BaseRegression

setModel

public final void setModel(java.lang.String model_type,
                           java.lang.String[] options)
                    throws java.lang.Exception

Set the underlying Weka-based model

Specified by:

setModel in interface WekaModel

Parameters:

model_type - Model type (ie trees.J48)

options - Options for the model

Throws:

java.lang.Exception

getModelName

public java.lang.String getModelName()

Return the model name

Specified by:

getModelName in interface WekaModel

Returns:

Name of Weka model used

getModelOptions

public java.lang.String[] getModelOptions()

Return the model options

Specified by:

getModelOptions in interface WekaModel

Returns:

Options of Weka model used

getModelFull

public java.lang.String getModelFull()

Return model name and options

Specified by:

getModelFull in interface WekaModel

Returns:

Name and options of Weka model used

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

train_protected

protected void train_protected(Dataset TrainingData)

Description copied from class: BaseModel

Train a model without evaluating performance

Specified by:

train_protected in class BaseModel

Parameters:

TrainingData - Training data

run_protected

public void run_protected(Dataset TestData)

Description copied from class: BaseModel

Run a model without checking if stuff is trained (use carefully)

Specified by:

run_protected in class BaseModel

Parameters:

TestData - Training data

getNFittingParameters

public int getNFittingParameters()

Description copied from interface: AbstractRegressionModel

Number of fitting parameters in a model. Only pertinent to nonlinear regression. Otherwise, this should just return 0.

Specified by:

getNFittingParameters in interface AbstractRegressionModel

Returns:

Number of fitting parameters

printModel_protected

protected java.lang.String printModel_protected()

Description copied from class: BaseModel

Internal method that handles printing the model as a string. Should end with a "\n"

Specified by:

printModel_protected in class BaseModel

Returns:

String representation of model

printModelDescriptionDetails

public java.util.List<java.lang.String> printModelDescriptionDetails(boolean htmlFormat)

Description copied from class: BaseModel

Print details of the model. Used by BaseModel.printDescription(boolean).

Implementation note: No not add indentation for details. That is handled by BaseModel.printDescription(boolean). You should also call the super operation to get the Normalizer and Attribute selector settings

Overrides:

printModelDescriptionDetails in class BaseModel

Parameters:

htmlFormat - Whether to use HTML format

Returns:

List describing model details. Each entry is a different line of the description (i.e., in place of newline characters).

getCitations

public java.util.List<org.apache.commons.lang3.tuple.Pair<java.lang.String,Citation>> getCitations()

Description copied from interface: Citable

Return a list of citations for this object and any underlying objects.

Specified by:

getCitations in interface Citable

Overrides:

getCitations in class BaseModel

Returns:

List of pairs: [Reason for Citation], [Citation]