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Dependents: RZ_A2M_Mbed_samples
ParamGrid Class Reference
[Machine Learning]
The structure represents the logarithmic grid range of statmodel parameters. More...
#include <ml.hpp>
Public Member Functions | |
| ParamGrid () | |
| Default constructor. | |
| ParamGrid (double _minVal, double _maxVal, double _logStep) | |
| Constructor with parameters. | |
Data Fields | |
| double | minVal |
| Minimum value of the statmodel parameter. Default value is 0. | |
| double | maxVal |
| Maximum value of the statmodel parameter. Default value is 0. | |
| double | logStep |
| Logarithmic step for iterating the statmodel parameter. | |
Detailed Description
The structure represents the logarithmic grid range of statmodel parameters.
It is used for optimizing statmodel accuracy by varying model parameters, the accuracy estimate being computed by cross-validation.
Definition at line 107 of file ml.hpp.
Constructor & Destructor Documentation
| ParamGrid | ( | ) |
Default constructor.
| ParamGrid | ( | double | _minVal, |
| double | _maxVal, | ||
| double | _logStep | ||
| ) |
Constructor with parameters.
Field Documentation
| double logStep |
Logarithmic step for iterating the statmodel parameter.
The grid determines the following iteration sequence of the statmodel parameter values:
![\[(minVal, minVal*step, minVal*{step}^2, \dots, minVal*{logStep}^n),\]](form_562.png)
where 
is the maximal index satisfying
![\[\texttt{minVal} * \texttt{logStep} ^n < \texttt{maxVal}\]](form_564.png)
The grid is logarithmic, so logStep must always be greater then 1. Default value is 1.
| double maxVal |
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