PLearn 0.1
Public Member Functions | Static Public Member Functions | Public Attributes | Static Public Attributes | Static Protected Member Functions | Private Types | Private Member Functions
PLearn::AnalyzeDond2DiscreteVariables Class Reference

Generate samples from a mixture of two gaussians. More...

#include <AnalyzeDond2DiscreteVariables.h>

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List of all members.

Public Member Functions

 AnalyzeDond2DiscreteVariables ()
 Default constructor.
int outputsize () const
 SUBCLASS WRITING: override this so that it returns the size of this learner's output, as a function of its inputsize(), targetsize() and set options.
void train ()
 *** SUBCLASS WRITING: ***
void computeOutput (const Vec &, Vec &) const
 *** SUBCLASS WRITING: ***
void computeCostsFromOutputs (const Vec &, const Vec &, const Vec &, Vec &) const
 *** SUBCLASS WRITING: ***
TVec< string > getTestCostNames () const
 *** SUBCLASS WRITING: ***
TVec< string > getTrainCostNames () const
 *** SUBCLASS WRITING: ***
virtual string classname () const
virtual OptionListgetOptionList () const
virtual OptionMapgetOptionMap () const
virtual RemoteMethodMapgetRemoteMethodMap () const
virtual
AnalyzeDond2DiscreteVariables
deepCopy (CopiesMap &copies) const
virtual void build ()
 Finish building the object; just call inherited::build followed by build_()
virtual void makeDeepCopyFromShallowCopy (CopiesMap &copies)
 Transforms a shallow copy into a deep copy.

Static Public Member Functions

static string _classname_ ()
static OptionList_getOptionList_ ()
static RemoteMethodMap_getRemoteMethodMap_ ()
static Object_new_instance_for_typemap_ ()
static bool _isa_ (const Object *o)
static void _static_initialize_ ()
static const PPathdeclaringFile ()

Public Attributes

string variable_name
 ### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //!
string target_name
 The field name of the target.
TVec< pair< real, real > > values_to_analyze
 The vector of values to check the correlation with the target.

Static Public Attributes

static StaticInitializer _static_initializer_

Static Protected Member Functions

static void declareOptions (OptionList &ol)
 Declares the class options.

Private Types

typedef PLearner inherited

Private Member Functions

void build_ ()
 This does the actual building.
void analyzeDiscreteVariable ()

Detailed Description

Generate samples from a mixture of two gaussians.

Definition at line 52 of file AnalyzeDond2DiscreteVariables.h.


Member Typedef Documentation

Reimplemented from PLearn::PLearner.

Definition at line 54 of file AnalyzeDond2DiscreteVariables.h.


Constructor & Destructor Documentation

PLearn::AnalyzeDond2DiscreteVariables::AnalyzeDond2DiscreteVariables ( )

Default constructor.

Definition at line 54 of file AnalyzeDond2DiscreteVariables.cc.

{
}

Member Function Documentation

string PLearn::AnalyzeDond2DiscreteVariables::_classname_ ( ) [static]

Reimplemented from PLearn::PLearner.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

OptionList & PLearn::AnalyzeDond2DiscreteVariables::_getOptionList_ ( ) [static]

Reimplemented from PLearn::PLearner.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

RemoteMethodMap & PLearn::AnalyzeDond2DiscreteVariables::_getRemoteMethodMap_ ( ) [static]

Reimplemented from PLearn::PLearner.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

bool PLearn::AnalyzeDond2DiscreteVariables::_isa_ ( const Object o) [static]

Reimplemented from PLearn::PLearner.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

Object * PLearn::AnalyzeDond2DiscreteVariables::_new_instance_for_typemap_ ( ) [static]

Reimplemented from PLearn::Object.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

StaticInitializer AnalyzeDond2DiscreteVariables::_static_initializer_ & PLearn::AnalyzeDond2DiscreteVariables::_static_initialize_ ( ) [static]

Reimplemented from PLearn::PLearner.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

void PLearn::AnalyzeDond2DiscreteVariables::analyzeDiscreteVariable ( ) [private]

Definition at line 114 of file AnalyzeDond2DiscreteVariables.cc.

References PLearn::TVec< T >::clear(), PLearn::endl(), PLearn::is_missing(), PLERROR, PLearn::TVec< T >::size(), and PLearn::ProgressBar::update().

{    
    // initialize primary dataset
    int main_length = train_set->length();
    int main_width = train_set->width();
    Vec main_input(main_width);
    TVec<string> main_names(main_width);
    main_names << train_set->fieldNames();
    
    // check for valid options
    int number_of_values = values_to_analyze.size();
    int variable_col = -1;
    int target_col = -1;
    for (int main_col = 0; main_col < main_width; main_col++)
    {
        if (variable_name == main_names[main_col]) variable_col = main_col;
        if (target_name == main_names[main_col]) target_col = main_col;
    }
    if (variable_col < 0) PLERROR("In AnalyzeDond2DiscreteVariables: variable name not found: %s", variable_name.c_str());
    if (target_col < 0) PLERROR("In AnalyzeDond2DiscreteVariables: target name not found: %s", target_name.c_str());
    if (number_of_values <= 0) PLERROR("In AnalyzeDond2DiscreteVariables: invalid values_to_analyze");
    
    // initialize working variables
    Vec value_target_sum(number_of_values);
    Vec value_present_count(number_of_values);
    value_target_sum.clear();
    value_present_count.clear();
    real target_sum = 0.0;
    real target_squared_sum = 0.0;
    real variable_present_count = 0.0;
    
    //Now, we can process the discrete variable.
    ProgressBar* pb = 0;
    pb = new ProgressBar( "Analyzing discrete variable " + variable_name, main_length);
    for (int main_row = 0; main_row < main_length; main_row++)
    {
        train_set->getRow(main_row, main_input);
        real variable_value = main_input[variable_col];
        if (is_missing(variable_value)) continue;
        real target_value = main_input[target_col];
        target_sum += target_value;
        target_squared_sum += target_value * target_value;
        variable_present_count += 1.0;
        for (int value_col = 0; value_col < number_of_values; value_col++)
        {
            if (variable_value < values_to_analyze[value_col].first || variable_value > values_to_analyze[value_col].second) continue;
            value_target_sum[value_col] += target_value;
            value_present_count[value_col] += 1.0;
        }
        pb->update( main_row );
    }
    delete pb;
    if (variable_present_count <= 0.0)
    {
        cout << "In AnalyzeDond2DiscreteVariables: no value present for this variable" << endl;
        return;
    }
    real target_mean = target_sum / variable_present_count;
    cout << "In AnalyzeDond2DiscreteVariables, for variable:  " << variable_name << endl;
    cout << variable_present_count << " values are present out of " << main_length << " samples." << endl;
    for (int value_col = 0; value_col < number_of_values; value_col++)
    {
        real ssxy = value_target_sum[value_col] - value_present_count[value_col] * target_mean;
        real ss2xy = ssxy * ssxy;
        real ssxx = value_present_count[value_col] * (1.0 -  value_present_count[value_col] / variable_present_count);
        real ssyy = target_squared_sum - target_sum * target_mean;
        real correlation_coefficient = ss2xy / (ssxx * ssyy);
        cout << "For value from: " << values_to_analyze[value_col].first << " to: " << values_to_analyze[value_col].second 
             << " occurence: " << value_present_count[value_col] << " correlation coefficient: " << correlation_coefficient << endl;
    }
}

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void PLearn::AnalyzeDond2DiscreteVariables::build ( ) [virtual]

Finish building the object; just call inherited::build followed by build_()

Reimplemented from PLearn::PLearner.

Definition at line 95 of file AnalyzeDond2DiscreteVariables.cc.

{
    // ### Nothing to add here, simply calls build_().
    inherited::build();
    build_();
}
void PLearn::AnalyzeDond2DiscreteVariables::build_ ( ) [private]

This does the actual building.

Reimplemented from PLearn::PLearner.

Definition at line 105 of file AnalyzeDond2DiscreteVariables.cc.

References PLERROR.

{
    if (train_set)
    {
        analyzeDiscreteVariable();
        PLERROR("AnalyzeDond2DiscreteVariables: we are done here");
    }
}
string PLearn::AnalyzeDond2DiscreteVariables::classname ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

void PLearn::AnalyzeDond2DiscreteVariables::computeCostsFromOutputs ( const Vec input,
const Vec output,
const Vec target,
Vec costs 
) const [virtual]

*** SUBCLASS WRITING: ***

This should be defined in subclasses to compute the weighted costs from already computed output. The costs should correspond to the cost names returned by getTestCostNames().

NOTE: In exotic cases, the cost may also depend on some info in the input, that's why the method also gets so see it.

Implements PLearn::PLearner.

Definition at line 189 of file AnalyzeDond2DiscreteVariables.cc.

{}
void PLearn::AnalyzeDond2DiscreteVariables::computeOutput ( const Vec input,
Vec output 
) const [virtual]

*** SUBCLASS WRITING: ***

This should be defined in subclasses to compute the output from the input.

Reimplemented from PLearn::PLearner.

Definition at line 188 of file AnalyzeDond2DiscreteVariables.cc.

{}
void PLearn::AnalyzeDond2DiscreteVariables::declareOptions ( OptionList ol) [static, protected]

Declares the class options.

Reimplemented from PLearn::PLearner.

Definition at line 61 of file AnalyzeDond2DiscreteVariables.cc.

References PLearn::OptionBase::buildoption, PLearn::declareOption(), target_name, values_to_analyze, and variable_name.

{

    declareOption(ol, "variable_name", &AnalyzeDond2DiscreteVariables::variable_name,
                  OptionBase::buildoption,
                  "The field name of the variable to be analyzed.");

    declareOption(ol, "target_name", &AnalyzeDond2DiscreteVariables::target_name,
                  OptionBase::buildoption,
                  "The field name of the target.");

    declareOption(ol, "values_to_analyze", &AnalyzeDond2DiscreteVariables::values_to_analyze,
                  OptionBase::buildoption,
                  "The vector of values to check the correlation with the target.\n"
                  "The algorithm groups the values from, to of each pair specified.\n");

    inherited::declareOptions(ol);
}

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static const PPath& PLearn::AnalyzeDond2DiscreteVariables::declaringFile ( ) [inline, static]

Reimplemented from PLearn::PLearner.

Definition at line 93 of file AnalyzeDond2DiscreteVariables.h.

:
    //#####  Protected Member Functions  ######################################
AnalyzeDond2DiscreteVariables * PLearn::AnalyzeDond2DiscreteVariables::deepCopy ( CopiesMap copies) const [virtual]

Reimplemented from PLearn::PLearner.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

OptionList & PLearn::AnalyzeDond2DiscreteVariables::getOptionList ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

OptionMap & PLearn::AnalyzeDond2DiscreteVariables::getOptionMap ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

RemoteMethodMap & PLearn::AnalyzeDond2DiscreteVariables::getRemoteMethodMap ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 49 of file AnalyzeDond2DiscreteVariables.cc.

TVec< string > PLearn::AnalyzeDond2DiscreteVariables::getTestCostNames ( ) const [virtual]

*** SUBCLASS WRITING: ***

This should return the names of the costs computed by computeCostsFromOutputs.

Implements PLearn::PLearner.

Definition at line 190 of file AnalyzeDond2DiscreteVariables.cc.

References PLearn::TVec< T >::append().

{
    TVec<string> result;
    result.append( "MSE" );
    return result;
}

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TVec< string > PLearn::AnalyzeDond2DiscreteVariables::getTrainCostNames ( ) const [virtual]

*** SUBCLASS WRITING: ***

This should return the names of the objective costs that the train method computes and for which it updates the VecStatsCollector train_stats.

Implements PLearn::PLearner.

Definition at line 196 of file AnalyzeDond2DiscreteVariables.cc.

References PLearn::TVec< T >::append().

{
    TVec<string> result;
    result.append( "MSE" );
    return result;
}

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void PLearn::AnalyzeDond2DiscreteVariables::makeDeepCopyFromShallowCopy ( CopiesMap copies) [virtual]

Transforms a shallow copy into a deep copy.

Reimplemented from PLearn::PLearner.

Definition at line 83 of file AnalyzeDond2DiscreteVariables.cc.

References PLearn::deepCopyField().

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int PLearn::AnalyzeDond2DiscreteVariables::outputsize ( ) const [virtual]

SUBCLASS WRITING: override this so that it returns the size of this learner's output, as a function of its inputsize(), targetsize() and set options.

Implements PLearn::PLearner.

Definition at line 186 of file AnalyzeDond2DiscreteVariables.cc.

{return 0;}
void PLearn::AnalyzeDond2DiscreteVariables::train ( ) [virtual]

*** SUBCLASS WRITING: ***

The role of the train method is to bring the learner up to stage==nstages, updating the stats with training costs measured on-line in the process.

TYPICAL CODE:

  static Vec input;  // static so we don't reallocate/deallocate memory each time...
  static Vec target; // (but be careful that static means shared!)
  input.resize(inputsize());    // the train_set's inputsize()
  target.resize(targetsize());  // the train_set's targetsize()
  real weight;
  
  if(!train_stats)   // make a default stats collector, in case there's none
      train_stats = new VecStatsCollector();
  
  if(nstages<stage)  // asking to revert to a previous stage!
      forget();      // reset the learner to stage=0
  
  while(stage<nstages)
  {
      // clear statistics of previous epoch
      train_stats->forget(); 
            
      //... train for 1 stage, and update train_stats,
      // using train_set->getSample(input, target, weight);
      // and train_stats->update(train_costs)
          
      ++stage;
      train_stats->finalize(); // finalize statistics for this epoch
  }

Implements PLearn::PLearner.

Definition at line 187 of file AnalyzeDond2DiscreteVariables.cc.

{}

Member Data Documentation

Reimplemented from PLearn::PLearner.

Definition at line 93 of file AnalyzeDond2DiscreteVariables.h.

The field name of the target.

Definition at line 67 of file AnalyzeDond2DiscreteVariables.h.

Referenced by declareOptions().

The vector of values to check the correlation with the target.

The algorithm groups the values from, to of each pair specified.

Definition at line 71 of file AnalyzeDond2DiscreteVariables.h.

Referenced by declareOptions().

### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //!

The field name of the variable to be analyzed.

Definition at line 64 of file AnalyzeDond2DiscreteVariables.h.

Referenced by declareOptions().


The documentation for this class was generated from the following files:
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