magpie.models.regression

Class BaseRegression

java.lang.Object

magpie.models.BaseModel

magpie.models.regression.BaseRegression

All Implemented Interfaces:

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

Direct Known Subclasses:

AbstractNonlinearRegression, ClassificationRegression, CompositeRegression, LASSORegression, LinearCorrectedRegression, MetallurgicalHeuristicRegression, MixingRuleRegression, MultiObjectiveRegression, PolynomialRegression, RandomGuessRegression, ScikitLearnRegression, SingleGuessRegression, StagedRegression, StructureKRRBasedRegression, WekaRegression

public abstract class BaseRegression
extends BaseModel
implements AbstractRegressionModel

Base class for all regression models.

Implemented Commands:

robust <Q> - Define False Positive Rate used for robust regression. See Motulsky and Brown
Q: Desired FPR during outlier detection.

See Also:

Serialized Form

Field Summary

Fields inherited from class magpie.models.BaseModel

AttributeSelector, trained, TrainingStats, validated, ValidationStats

Constructor Summary

Constructors

Constructor and Description
BaseRegression()

Method Summary

Modifier and Type	Method and Description
BaseRegression	clone()
boolean	doRobustRegression() Whether robust regression is desired.
double	getRobustRegressionQ() Get desired False Discovery Rate
void	robustTraining(Dataset TrainData) Robustly train a model.
java.lang.Object	runCommand(java.util.List<java.lang.Object> Command) Process some command described by a list of Objects.
void	setRobustRegressionQ(double Q) Set the desired False Discovery Rate for outlier detection.

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_protected, printModel, printModelDescriptionDetails, resetModel, run_protected, run, saveCommand, saveState, setAttributeSelector, setComponent, setFilter, train_protected, train, train

Methods inherited from class java.lang.Object

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

Methods inherited from interface magpie.models.regression.AbstractRegressionModel

getNFittingParameters

Methods inherited from interface magpie.utility.interfaces.Options

printUsage, setOptions

Constructor Detail

BaseRegression

public BaseRegression()

Method Detail

clone

public BaseRegression clone()

Overrides:

clone in class BaseModel

robustTraining

public void robustTraining(Dataset TrainData)

Description copied from interface: AbstractRegressionModel

Robustly train a model. Is called from BaseModel.train(magpie.data.Dataset).

I recommend that you use methods outlined in a paper by Motulsky and Brown.

.

Specified by:

robustTraining in interface AbstractRegressionModel

Parameters:

TrainData - Training data

setRobustRegressionQ

public void setRobustRegressionQ(double Q)

Description copied from interface: AbstractRegressionModel

Set the desired False Discovery Rate for outlier detection. A robust regression parameter of 0.01 is recommended. Zero turns it off. Don't give it less than zero.

See paper by Benjamini and Hochberg

Specified by:

setRobustRegressionQ in interface AbstractRegressionModel

Parameters:

Q - Desired FDR

getRobustRegressionQ

public double getRobustRegressionQ()

Description copied from interface: AbstractRegressionModel

Get desired False Discovery Rate

Specified by:

getRobustRegressionQ in interface AbstractRegressionModel

Returns:

Target FDR

doRobustRegression

public boolean doRobustRegression()

Description copied from interface: AbstractRegressionModel

Whether robust regression is desired. For now, this should be:
getRobustRegressionQ > 0

Specified by:

doRobustRegression in interface AbstractRegressionModel

runCommand

public java.lang.Object runCommand(java.util.List<java.lang.Object> Command)
                            throws java.lang.Exception

Description copied from interface: Commandable

Process some command described by a list of Objects.

Specified by:

runCommand in interface Commandable

Overrides:

runCommand in class BaseModel

Parameters:

Command - Command as a list of objects

Returns:

Any output (null if no output generated by command)

Throws:

java.lang.Exception - If something goes wrong