magpie.models.regression

Class NonlinearRegressionExpr

java.lang.Object

magpie.models.BaseModel

magpie.models.regression.BaseRegression

magpie.models.regression.AbstractNonlinearRegression

magpie.models.regression.AbstractParsedNonlinearRegression

magpie.models.regression.NonlinearRegressionExpr

All Implemented Interfaces:

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

public class NonlinearRegressionExpr
extends AbstractParsedNonlinearRegression

Performs non-linear regression on a function supplied as a string. Uses a modified version of the Expr library, which should have been provided with this software.

Formatting rules are shown in AbstractParsedNonlinearRegression.

Usage: <equation to be fit...>
equation: Equation to be fit. See Javadoc of AbstractParsedNonlinearRegression for details.

See Also:

Serialized Form

Field Summary

Fields inherited from class magpie.models.regression.AbstractParsedNonlinearRegression

UserFormula

Fields inherited from class magpie.models.BaseModel

AttributeSelector, trained, TrainingStats, validated, ValidationStats

Constructor Summary

Constructors

Constructor and Description
NonlinearRegressionExpr()

Method Summary

Modifier and Type	Method and Description
protected java.lang.String	defineVariables(java.lang.String Expression) Reads an expression and stores the names of all variables.
protected double	function(double[] variables, double[] coeff) Function defined by the user.
void	prepareEvaluator(java.lang.String Expression) Define the internal Evaluator and parse the user-defined function

Methods inherited from class magpie.models.regression.AbstractParsedNonlinearRegression

defineCoefficients, defineVariables, parseFormula, printModel_protected, printModelDescriptionDetails, printUsage, setOptions

Methods inherited from class magpie.models.regression.AbstractNonlinearRegression

addCoefficient, addCoefficient, addVariable, 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

Constructor Detail

NonlinearRegressionExpr

public NonlinearRegressionExpr()

Method Detail

defineVariables

protected 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

Specified by:

defineVariables in class AbstractParsedNonlinearRegression

Parameters:

Expression - Expression to be parsed

Returns:

Expression in a form usable by Expr

Throws:

java.lang.Exception - If poorly-formed expression

prepareEvaluator

public void prepareEvaluator(java.lang.String Expression)
                      throws expr.SyntaxException

Define the internal Evaluator and parse the user-defined function

Specified by:

prepareEvaluator in class AbstractParsedNonlinearRegression

Parameters:

Expression - User-defined function

Throws:

expr.SyntaxException - If the formula is illegible

function

protected double function(double[] variables,
                          double[] coeff)

Description copied from class: AbstractNonlinearRegression

Function defined by the user. Program supplies attributes in the same order as defined in AbstractNonlinearRegression.defineVariables().

Specified by:

function in class AbstractNonlinearRegression

Parameters:

variables - Values of attributes used as independent variables

coeff - Coefficients of equation

Returns:

Value of equation given those inputs