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

#include <NearestNeighborPredictionCost.h>

Inheritance diagram for PLearn::NearestNeighborPredictionCost:
Inheritance graph
[legend]
Collaboration diagram for PLearn::NearestNeighborPredictionCost:
Collaboration graph
[legend]

List of all members.

Public Member Functions

 NearestNeighborPredictionCost ()
 Default constructor.
virtual string classname () const
virtual OptionListgetOptionList () const
virtual OptionMapgetOptionMap () const
virtual RemoteMethodMapgetRemoteMethodMap () const
virtual
NearestNeighborPredictionCost
deepCopy (CopiesMap &copies) const
virtual void build ()
 Post-constructor.
void run ()
 Override this for runnable objects (default method issues a runtime error).
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

int knn
VMat test_set
string learner_spec
Vec cost
VMat computed_outputs

Static Public Attributes

static StaticInitializer _static_initializer_

Static Protected Member Functions

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

Protected Attributes

PP< PLearnerlearner

Private Types

typedef Object inherited

Private Member Functions

void build_ ()
 This does the actual building.

Detailed Description

Definition at line 54 of file NearestNeighborPredictionCost.h.


Member Typedef Documentation

Reimplemented from PLearn::Object.

Definition at line 59 of file NearestNeighborPredictionCost.h.


Constructor & Destructor Documentation

PLearn::NearestNeighborPredictionCost::NearestNeighborPredictionCost ( )

Default constructor.

Definition at line 57 of file NearestNeighborPredictionCost.cc.

                                                             : test_set(AutoVMatrix("/u/monperrm/data/amat/gauss2D_200_0p001_1.amat"))
    /* ### Initialize all fields to their default value */
{
    // ...

    // ### You may or may not want to call build_() to finish building the object
    // build_();
}

Member Function Documentation

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Post-constructor.

The normal implementation should call simply inherited::build(), then this class's build_(). This method should be callable again at later times, after modifying some option fields to change the "architecture" of the object.

Reimplemented from PLearn::Object.

Definition at line 146 of file NearestNeighborPredictionCost.cc.

References PLearn::Object::build(), and build_().

Here is the call graph for this function:

void PLearn::NearestNeighborPredictionCost::build_ ( ) [private]

This does the actual building.

Reimplemented from PLearn::Object.

Definition at line 92 of file NearestNeighborPredictionCost.cc.

References computed_outputs, cost, knn, learner, learner_spec, PLearn::VMat::length(), PLearn::Object::load(), PLearn::TVec< T >::resize(), and test_set.

Referenced by build().

{
    // ### This method should do the real building of the object,
    // ### according to set 'options', in *any* situation. 
    // ### Typical situations include:
    // ###  - Initial building of an object from a few user-specified options
    // ###  - Building of a "reloaded" object: i.e. from the complete set of all serialised options.
    // ###  - Updating or "re-building" of an object after a few "tuning" options have been modified.
    // ### You should assume that the parent class' build_() has already been called.
  
    PLearn::load(learner_spec,learner);
    learner->report_progress = false;
    cost.resize(knn);
    cost<<0;
    computed_outputs = new MemoryVMatrix(test_set->length(),learner->outputsize());
    learner->use(test_set,computed_outputs);

}

Here is the call graph for this function:

Here is the caller graph for this function:

string PLearn::NearestNeighborPredictionCost::classname ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

void PLearn::NearestNeighborPredictionCost::declareOptions ( OptionList ol) [static, protected]

Declares this class' options.

Reimplemented from PLearn::Object.

Definition at line 68 of file NearestNeighborPredictionCost.cc.

References PLearn::OptionBase::buildoption, PLearn::declareOption(), PLearn::Object::declareOptions(), knn, learner_spec, and test_set.

{
    // ### Declare all of this object's options here
    // ### For the "flags" of each option, you should typically specify  
    // ### one of OptionBase::buildoption, OptionBase::learntoption or 
    // ### OptionBase::tuningoption. Another possible flag to be combined with
    // ### is OptionBase::nosave

    declareOption(ol, "knn", &NearestNeighborPredictionCost::knn, OptionBase::buildoption,
                  "Help text describing this option");
    declareOption(ol, "test_set", &NearestNeighborPredictionCost::test_set, OptionBase::buildoption,
                  "Help text describing this option");
    declareOption(ol, "learner_spec", &NearestNeighborPredictionCost::learner_spec, OptionBase::buildoption,
                  "Help text describing this option");
  
// ### ex:
    // declareOption(ol, "myoption", &NearestNeighborPredictionCost::myoption, OptionBase::buildoption,
    //               "Help text describing this option");
    // ...

    // Now call the parent class' declareOptions
    inherited::declareOptions(ol);
}

Here is the call graph for this function:

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

Reimplemented from PLearn::Object.

Definition at line 111 of file NearestNeighborPredictionCost.h.

NearestNeighborPredictionCost * PLearn::NearestNeighborPredictionCost::deepCopy ( CopiesMap copies) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Reimplemented from PLearn::Object.

Definition at line 66 of file NearestNeighborPredictionCost.cc.

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

Transforms a shallow copy into a deep copy.

Reimplemented from PLearn::Object.

Definition at line 152 of file NearestNeighborPredictionCost.cc.

References PLearn::Object::makeDeepCopyFromShallowCopy(), and PLERROR.

{
    inherited::makeDeepCopyFromShallowCopy(copies);

    // ### Call deepCopyField on all "pointer-like" fields 
    // ### that you wish to be deepCopied rather than 
    // ### shallow-copied.
    // ### ex:
    // deepCopyField(trainvec, copies);

    // ### Remove this line when you have fully implemented this method.
    PLERROR("NearestNeighborPredictionCost::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
}

Here is the call graph for this function:

void PLearn::NearestNeighborPredictionCost::run ( ) [virtual]

Override this for runnable objects (default method issues a runtime error).

Runnable objects are objects that can be used as *THE* object of a .plearn script. The run() method specifies what they should do when executed.

Reimplemented from PLearn::Object.

Definition at line 111 of file NearestNeighborPredictionCost.cc.

References computed_outputs, cost, PLearn::endl(), i, j, knn, learner, PLearn::VMat::length(), PLearn::local_neighbors_differences(), PLearn::min(), n, PLearn::projection_error(), test_set, and PLearn::VMat::width().

{

    VMat targets_vmat;
    int l = test_set->length();
    int n = test_set->width();
    int n_dim = learner->outputsize() / test_set->width();
    Var targets = Var(1,n);
    Var prediction = Var(n_dim,n);
    Var proj_err = projection_error(prediction, targets, 0, n);
    Func projection_error_f =  Func(prediction & targets, proj_err);
    Vec temp(n_dim*n);
    Vec temp2(n);

    for (int j=0; j<knn; ++j)
    {
        targets_vmat = local_neighbors_differences(test_set, j+1, true);
        for (int i=0;i<l;++i)
        {
            computed_outputs->getRow(i,temp);
            targets_vmat->getRow(i,temp2);
            //cout<<temp2<<"/ "<<temp<<" "<<dot(temp,temp2)<<endl;
            //cout<<projection_error_f(temp,temp2)<<endl;
            cost[j]+=projection_error_f(temp,temp2);
        }
    }
    cost/=l;
    cout<<"Cost = "<<cost<<endl;
    cout<<min(cost)<<endl;
//   printf("%.12f",cost);

}

Here is the call graph for this function:


Member Data Documentation

Reimplemented from PLearn::Object.

Definition at line 111 of file NearestNeighborPredictionCost.h.

Definition at line 82 of file NearestNeighborPredictionCost.h.

Referenced by build_(), and run().

Definition at line 81 of file NearestNeighborPredictionCost.h.

Referenced by build_(), and run().

Definition at line 76 of file NearestNeighborPredictionCost.h.

Referenced by build_(), declareOptions(), and run().

Definition at line 68 of file NearestNeighborPredictionCost.h.

Referenced by build_(), and run().

Definition at line 78 of file NearestNeighborPredictionCost.h.

Referenced by build_(), and declareOptions().

Definition at line 77 of file NearestNeighborPredictionCost.h.

Referenced by build_(), declareOptions(), and run().


The documentation for this class was generated from the following files:
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines