EM strategy for pixel-based classification. This is an unsupervised and pixel-based classification algorithm. Expectation-Maximization (EM) works iteratively by applying two steps: the E-step (Expectation) and the M-step (Maximization). The method aims to approximate the parameter estimates to real data distribution, along the iterations:  
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#include <ClassifierEMStrategy.h>
EM strategy for pixel-based classification. This is an unsupervised and pixel-based classification algorithm. Expectation-Maximization (EM) works iteratively by applying two steps: the E-step (Expectation) and the M-step (Maximization). The method aims to approximate the parameter estimates to real data distribution, along the iterations: 
- The E-step calculates the conditional expectation of the complete a posteriori probability function.
 
- The M-step updates the parameter estimation. 
 
Definition at line 58 of file ClassifierEMStrategy.h.
 
      
        
          | te::rp::ClassifierEMStrategy::ClassifierEMStrategy  | 
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          | te::rp::ClassifierEMStrategy::~ClassifierEMStrategy  | 
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          | bool te::rp::ClassifierEMStrategy::execute  | 
          ( | 
          const te::rst::Raster &  | 
          inputRaster,  | 
         
        
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          const std::vector< unsigned int > &  | 
          inputRasterBands,  | 
         
        
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          const std::vector< te::gm::Polygon * > &  | 
          inputPolygons,  | 
         
        
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          te::rst::Raster &  | 
          outputRaster,  | 
         
        
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          const unsigned int  | 
          outputRasterBand,  | 
         
        
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          const bool  | 
          enableProgressInterface  | 
         
        
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          ) | 
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          | throw  | ( | te::rp::Exception | 
         
        
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virtual   | 
  
 
Executes the classification strategy. 
- Parameters
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    | inputRaster | Input raster.  | 
    | inputRasterBands | Input raster bands.  | 
    | inputPolygons | The polygons to be classified when using object-based image analysis (OBIA).  | 
    | outputRaster | Output raster.  | 
    | outputRasterBand | Output raster band.  | 
    | enableProgressInterface | Enable the internal strategy to update the progress interface. | 
  
   
- Returns
 - true if OK, false on errors. 
 
Implements te::rp::ClassifierStrategy.
 
 
  
  
      
        
          | std::vector< int > te::rp::ClassifierEMStrategy::getOutputDataTypes  | 
          ( | 
           | ) | 
           const | 
         
       
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virtual   | 
  
 
Returns the output raster pixel data type for each output band. 
- Returns
 - Returns the output raster pixel data type for each output band. 
 
Implements te::rp::ClassifierStrategy.
 
 
Initialize the classification strategy. 
- Parameters
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    | strategyParams | A pointer to the user given specific classification strategy parameters ou NULL if no parameters are present. | 
  
   
- Returns
 - true if OK, false on errors. 
 
Implements te::rp::ClassifierStrategy.
 
 
  
  
      
        
          | bool te::rp::ClassifierEMStrategy::m_isInitialized | 
         
       
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protected   | 
  
 
 
The documentation for this class was generated from the following file: