MAP strategy for classification.
More...
#include <MAP.h>
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bool | classify (const InputAdaptor< double > &input, const std::vector< unsigned int > &attributesIndices, const std::vector< double > &inputNoDataValues, OutputAdaptor< unsigned int > &output, const unsigned int outputIndex, const double outputNoDataValue, const bool enableProgressInterface) throw (te::cl::Exception) |
| Classify an input iterated data and save the result on the output iterated data. More...
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bool | initialize (const Parameters ¶ms) throw (te::cl::Exception) |
| Initialize this classifier instance with new parameters. More...
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| MAP () |
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bool | train (const InputAdaptor< double > &samples, const std::vector< unsigned int > &attributesIndices, const std::vector< unsigned int > &sampleLabels, const bool enableProgressInterface) throw (te::cl::Exception) |
| Train this classifier instance using the initialization parameters and the suppied train data. More...
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| ~MAP () |
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bool | getPrioriProbabilities (const InputAdaptor< double > &input, const std::vector< unsigned int > &attributesIndices, std::vector< double > &prioriProbs) const |
| Calculate priori probabilities by pre-classifying the input data. More...
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void | reset () |
| Reset this instance to its initial state. More...
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MAP strategy for classification.
Definition at line 54 of file MAP.h.
bool te::cl::MAP::classify |
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const InputAdaptor< double > & |
input, |
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const std::vector< unsigned int > & |
attributesIndices, |
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const std::vector< double > & |
inputNoDataValues, |
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OutputAdaptor< unsigned int > & |
output, |
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const unsigned int |
outputIndex, |
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const double |
outputNoDataValue, |
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const bool |
enableProgressInterface |
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throw | ( | te::cl::Exception |
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Classify an input iterated data and save the result on the output iterated data.
- Parameters
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input | Input data to be classified. |
attributesIndices | The attributes indexes to processe from the iterated train data. |
inputNoDataValues | A vector of no-data values for each attribute dimension or an empty vector if no-data values are not used. |
output | Output classified data. |
outputIndex | The output attribute index. |
outputNoDataValue | A output label value to use when dealing with input no-data. |
enableProgressInterface | Enable/disable the use of a proress interfece. |
bool te::cl::MAP::getPrioriProbabilities |
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const InputAdaptor< double > & |
input, |
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const std::vector< unsigned int > & |
attributesIndices, |
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std::vector< double > & |
prioriProbs |
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Calculate priori probabilities by pre-classifying the input data.
- Parameters
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input | Input data to be classified. |
attributesIndices | The attributes indexes to processe from the iterated train data. |
prioriProbs | Calculated priori-probabilities. |
bool te::cl::MAP::initialize |
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const Parameters & |
params | ) |
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throw | ( | te::cl::Exception |
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Initialize this classifier instance with new parameters.
- Parameters
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params | New initialization parameters. |
void te::cl::MAP::reset |
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Reset this instance to its initial state.
bool te::cl::MAP::train |
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const InputAdaptor< double > & |
samples, |
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const std::vector< unsigned int > & |
attributesIndices, |
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const std::vector< unsigned int > & |
sampleLabels, |
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const bool |
enableProgressInterface |
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throw | ( | te::cl::Exception |
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Train this classifier instance using the initialization parameters and the suppied train data.
- Parameters
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samples | Train data samples. |
attributesIndices | The attributes indexes to processe from the iterated train data. |
sampleLabels | The sample lables for each iterated train data element. |
enableProgressInterface | Enable/disable the use of a proress interfece. |
std::vector< boost::numeric::ublas::matrix< double > > te::cl::MAP::m_classesCovarianceInvMatrixes |
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Classes covariance inverse matrixes.
Definition at line 131 of file MAP.h.
std::vector< boost::numeric::ublas::matrix< double > > te::cl::MAP::m_classesCovarianceMatrixes |
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Classes covariance matrixes.
Definition at line 130 of file MAP.h.
std::vector< std::vector< double > > te::cl::MAP::m_classesMeans |
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Classes means;.
Definition at line 129 of file MAP.h.
std::vector< double > te::cl::MAP::m_classesOptizedMAPDiscriminantTerm |
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An optimized portion of the MAP discriminant function.
Definition at line 133 of file MAP.h.
std::vector<unsigned int> te::cl::MAP::m_classLabels |
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class labels
Definition at line 132 of file MAP.h.
bool te::cl::MAP::m_isInitialized |
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True if this instance is initialized.
Definition at line 127 of file MAP.h.
Internal execution parameters.
Definition at line 128 of file MAP.h.
The documentation for this class was generated from the following file:
- /home/castejon/castejon_files/develop/terralib5/git_master/src/terralib/classification/MAP.h