magpie.models.regression

Class SingleGuessRegression

java.lang.Object

magpie.models.BaseModel

magpie.models.regression.BaseRegression

magpie.models.regression.SingleGuessRegression

All Implemented Interfaces:

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

Direct Known Subclasses:

GuessMeanRegression

public class SingleGuessRegression
extends BaseRegression

Guess a single, user-specified value for the class variable of all entries.

User can add jitter to the guess, which adds a small random value to the guess. This has the effect of forcing the entries to be randomly ranked by an BaseEntryRanker, but without changing the actual guess by that much. The actual size of this step is set by the value of Jitter.

Usage: <guess> [-jitter <jitter>]
guess: Predicted value to use for each entry
value: Amount of random variation added to guess (default=0)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected double	Guess Guess for all classes
protected double	Jitter Amount of jitter added to the answer

Fields inherited from class magpie.models.BaseModel

AttributeSelector, trained, TrainingStats, validated, ValidationStats

Constructor Summary

Constructors

Constructor and Description
SingleGuessRegression()

Method Summary

Modifier and Type	Method and Description
SingleGuessRegression	clone()
double	getGuess() Get the user's guess
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 E) Run a model without checking if stuff is trained (use carefully)
void	setGuess(double x) Sets the user's guess
void	setOptions(java.util.List OptionsObj) Set any options for this object.
void	train_protected(Dataset E) 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, getCitations, 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, toString, wait, wait, wait

Field Detail

Guess

protected double Guess

Guess for all classes

Jitter

protected double Jitter

Amount of jitter added to the answer

Constructor Detail

SingleGuessRegression

public SingleGuessRegression()

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.

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: ".

Returns:

Usage for this function

setGuess

public void setGuess(double x)

Sets the user's guess

Parameters:

x - Desired guess

getGuess

public double getGuess()

Get the user's guess

Returns:

Currently-used guess

clone

public SingleGuessRegression clone()

Overrides:

clone in class BaseRegression

train_protected

public void train_protected(Dataset E)

Description copied from class: BaseModel

Train a model without evaluating performance

Specified by:

train_protected in class BaseModel

Parameters:

E - Training data

run_protected

public void run_protected(Dataset E)

Description copied from class: BaseModel

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

Specified by:

run_protected in class BaseModel

Parameters:

E - 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.

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).