magpie.models.regression

Class AbstractParsedNonlinearRegression

java.lang.Object

magpie.models.BaseModel

magpie.models.regression.BaseRegression

magpie.models.regression.AbstractNonlinearRegression

magpie.models.regression.AbstractParsedNonlinearRegression

All Implemented Interfaces:

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

Direct Known Subclasses:

NonlinearRegressionExpr

public abstract class AbstractParsedNonlinearRegression
extends AbstractNonlinearRegression

Superclass of AbstractNonlinearRegression-based models which parse the equation of interest from text input.

Use this class by passing a specially-formatted equation to #parseFormula(java.lang.String) .

Usage: <equation>
equation: Equation to be fitted. See Javadoc for rules.

Rules for writing an equation:

• Variables are attributes from a dataset, and must be defined using the notation: #{a:<Attribute Name>}
• Fitting constants must be defined using the expression: #{<Constant Name>}

Example expression with two fitting constants and a single attribute variable : #{a} + #{b} * #{a:NComp}

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected java.lang.String	UserFormula Stores the user-provided formula

Fields inherited from class magpie.models.BaseModel

AttributeSelector, trained, TrainingStats, validated, ValidationStats

Constructor Summary

Constructors

Constructor and Description
AbstractParsedNonlinearRegression()

Method Summary

Modifier and Type	Method and Description
protected void	defineCoefficients() Define the names and, if desired, initial guesses of fitting coefficients.
protected void	defineVariables() Define which attributes are used by the function.
protected abstract java.lang.String	defineVariables(java.lang.String Expression) Reads an expression and stores the names of all variables.
void	parseFormula(java.lang.String formula) Parse formula to use as model.
abstract void	prepareEvaluator(java.lang.String Expression) Define the internal Evaluator and parse the user-defined function
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	setOptions(java.util.List OptionsObj) Set any options for this object.

Methods inherited from class magpie.models.regression.AbstractNonlinearRegression

addCoefficient, addCoefficient, addVariable, function, getCoefficientName, getFittedCoefficient, getMaxIter, getNFittingParameters, getVariableName, makeObjectiveFunction, NCoefficients, NVariables, run_protected, runCommand, runNonlinearCommand, setInitialGuess, setMaxIterations, train_protected

Methods inherited from class magpie.models.regression.BaseRegression

clone, doRobustRegression, getRobustRegressionQ, robustTraining, 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

UserFormula

protected java.lang.String UserFormula

Stores the user-provided formula

Constructor Detail

AbstractParsedNonlinearRegression

public AbstractParsedNonlinearRegression()

Method Detail

defineCoefficients

protected void defineCoefficients()

Description copied from class: AbstractNonlinearRegression

Define the names and, if desired, initial guesses of fitting coefficients. As long as coefficients are defined by the time this program exits, it does not matter what this code actually does (i.e. you can define coefficients in other functions).

Coefficients are defined using the AbstractNonlinearRegression.addCoefficient(java.lang.String) function.

In AbstractNonlinearRegression.function(double[], double[]) these names are mapped to the coeff array in the same order you define them.

Specified by:

defineCoefficients in class AbstractNonlinearRegression

defineVariables

protected abstract java.lang.String defineVariables(java.lang.String Expression)
                                             throws java.lang.Exception

Reads an expression and stores the names of all variables. Also sets the required fields of AbstractNonlinearRegression

Parameters:

Expression - Expression to be parsed

Returns:

Expression in a form usable by Expr

Throws:

java.lang.Exception - If poorly-formed expression

defineVariables

protected void defineVariables()

Description copied from class: AbstractNonlinearRegression

Define which attributes are used by the function. This function is run a single time during training. As long as variables are defined by the time this function is complete, it does not matter how your code actually does it.

Variables are defined using the AbstractNonlinearRegression.addVariable(java.lang.String) function. *

In AbstractNonlinearRegression.function(double[], double[]) these names are mapped to the variable array in the same order you define them.

Specified by:

defineVariables in class AbstractNonlinearRegression

prepareEvaluator

public abstract void prepareEvaluator(java.lang.String Expression)
                               throws java.lang.Exception

Define the internal Evaluator and parse the user-defined function

Parameters:

Expression - User-defined function

Throws:

java.lang.Exception - If the formula is illegible

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

Overrides:

setOptions in class AbstractNonlinearRegression

Parameters:

OptionsObj - Array of options as Objects - can be null

Throws:

java.lang.Exception - if problem with inputs

parseFormula

public void parseFormula(java.lang.String formula)
                  throws java.lang.Exception

Parse formula to use as model. See description of AbstractParsedNonlinearRegression for rules.

Parameters:

formula - Formula to be parsed

Throws:

java.lang.Exception

See Also:

AbstractParsedNonlinearRegression

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

Overrides:

printUsage in class AbstractNonlinearRegression

Returns:

Usage for this function

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).

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