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Calculates model parameter estimates from logistic regression data using the Levenberg-Marquardt method. More...
#include <rw/analytics/loglevbg.h>
Public Member Functions | |
RWLogisticLevenbergMarquardt () | |
RWLogisticLevenbergMarquardt (const RWLogisticLevenbergMarquardt &rhs) | |
virtual void | calc (const RWGenMat< double > &predictors, const RWMathVec< bool > &observations) |
virtual void | setBaseCalc (const RWGenMat< double > &r, const RWMathVec< bool > &o) |
virtual RWMathVec< double > | parameters () const |
virtual void | addPredToBaseCalc (const RWAddPredictors< double, bool > &dataChange) |
virtual void | removePredFromBaseCalc (const RWRemovePredictors< double, bool > &dataChange) |
virtual void | addObsToBaseCalc (const RWAddObservations< double, bool > &dataChange) |
virtual void | removeObsFromBaseCalc (const RWRemoveObservations< double, bool > &dataChange) |
virtual bool | fail () const |
virtual RWCString | name () const |
virtual RWRegressionCalc < double, bool > * | clone () const |
RWLogisticLevenbergMarquardt & | operator= (const RWLogisticLevenbergMarquardt &) |
Class RWLogisticLevenbergMarquardt calculates model parameter estimates from logistic regression data using the Levenberg-Marquardt method, described in the Business Analysis Module User's Guide.
#include <rw/analytics/loglevbg.h> RWLogisticLevenbergMarquardt c;
#include <rw/analytics/loglevbg.h> #include <iostream> int main() { RWGenMat<double> predData = "5x2 [1 234 2 431 3 333 4 654 5 788]"; RWMathVec<bool> obsData(5, rwUninitialized ); obsData[0] = obsData[3] = obsData[4] = true; obsData[1] = obsData[2] = false; RWLogisticLevenbergMarquardt mlCalc; mlCalc.calc( predData, obsData ); if ( !mlCalc.fail() ) { std::cout << "Parameters:" << mlCalc.parameters() << std::endl; } else { std::cout << "Calculation failed" << std::endl; } return 0; }
RWLogisticLevenbergMarquardt::RWLogisticLevenbergMarquardt | ( | ) | [inline] |
Constructs an empty RWLogisticLevenbergMarquardt object.
RWLogisticLevenbergMarquardt::RWLogisticLevenbergMarquardt | ( | const RWLogisticLevenbergMarquardt & | rhs | ) | [inline] |
Copy constructor.
virtual void RWLogisticLevenbergMarquardt::addObsToBaseCalc | ( | const RWAddObservations< double, bool > & | dataChange | ) | [inline, virtual] |
Recalculates the regression model using an additional set of predictor-observation data pairs. This method offers the option of using results from the base calculation to calculate the coefficients for the larger data set. Consequently, this method can be called only when a base calculation has been set using setBaseCalc(). The input variable provides the additional data.
Reimplemented from RWRegressionCalc< double, bool >.
virtual void RWLogisticLevenbergMarquardt::addPredToBaseCalc | ( | const RWAddPredictors< double, bool > & | dataChange | ) | [virtual] |
Expands the regression model to include new predictor variables. This method offers the option of using results from the base calculation to calculate the coefficients for the larger predictor set. Consequently, this method can be called only when a base calculation has been set using setBaseCalc(). The input variable contains the data for the added predictor variables.
Reimplemented from RWRegressionCalc< double, bool >.
virtual void RWLogisticLevenbergMarquardt::calc | ( | const RWGenMat< double > & | predictors, | |
const RWMathVec< bool > & | observations | |||
) | [virtual] |
Calculates the parameters for the regression model. Invoking this method does not affect the state of any existing base calculation.
Implements RWRegressionCalc< double, bool >.
virtual RWRegressionCalc<double,bool>* RWLogisticLevenbergMarquardt::clone | ( | ) | const [inline, virtual] |
Allocates and creates a clone, or exact copy, of the current instance, and returns a pointer to the copy. Caller is responsible for deleting the returned object.
Implements RWRegressionCalc< double, bool >.
virtual bool RWLogisticLevenbergMarquardt::fail | ( | ) | const [inline, virtual] |
Returns true
if the calculation failed.
Implements RWRegressionCalc< double, bool >.
virtual RWCString RWLogisticLevenbergMarquardt::name | ( | ) | const [inline, virtual] |
Returns the name of the calculation method.
Implements RWRegressionCalc< double, bool >.
RWLogisticLevenbergMarquardt& RWLogisticLevenbergMarquardt::operator= | ( | const RWLogisticLevenbergMarquardt & | ) |
Assignment operator.
virtual RWMathVec<double> RWLogisticLevenbergMarquardt::parameters | ( | ) | const [virtual] |
Returns the parameters from the last calculation performed. If the calculation failed, and this method is called, an exception of type RWInternalErr is thrown.
Implements RWRegressionCalc< double, bool >.
virtual void RWLogisticLevenbergMarquardt::removeObsFromBaseCalc | ( | const RWRemoveObservations< double, bool > & | dataChange | ) | [inline, virtual] |
Modifies the regression model by removing a set of contiguous predictor-observation data pairs, and recalculating the parameters. This method offers the option of using results from the base calculation to calculate the coefficients for the smaller data set. Consequently, this method can be called only when a base calculation has been set using setBaseCalc(). The input variable indicates the indices of the rows to be removed from the regression matrix and from the observation vector used in the base calculation.
Reimplemented from RWRegressionCalc< double, bool >.
virtual void RWLogisticLevenbergMarquardt::removePredFromBaseCalc | ( | const RWRemovePredictors< double, bool > & | dataChange | ) | [virtual] |
Shrinks the regression model to exclude previously used predictor variables. This method offers the option of using results from the base calculation to calculate the coefficients for the smaller predictor set. Consequently, this method can be called only when a base calculation has been set using setBaseCalc(). The input variable indicates the indices of the columns to be removed from the regression matrix used in the base calculation.
Reimplemented from RWRegressionCalc< double, bool >.
virtual void RWLogisticLevenbergMarquardt::setBaseCalc | ( | const RWGenMat< double > & | r, | |
const RWMathVec< bool > & | o | |||
) | [virtual] |
Calculates the coefficients for the input regression data and sets the base calculation to this calculation.
Reimplemented from RWRegressionCalc< double, bool >.
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