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PLearn 0.1
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The first sentence should be a BRIEF DESCRIPTION of what the class does. More...
#include <RankingFromKernel.h>


Public Member Functions | |
| RankingFromKernel () | |
| Default constructor. | |
| virtual int | outputsize () const |
| Returns the size of this learner's output, (which typically may depend on its inputsize(), targetsize() and set options). | |
| virtual void | forget () |
| (Re-)initializes the PLearner in its fresh state (that state may depend on the 'seed' option) and sets 'stage' back to 0 (this is the stage of a fresh learner!). | |
| virtual void | train () |
| The role of the train method is to bring the learner up to stage==nstages, updating the train_stats collector with training costs measured on-line in the process. | |
| virtual void | computeOutput (const Vec &input, Vec &output) const |
| Computes the output from the input. | |
| virtual void | computeCostsFromOutputs (const Vec &input, const Vec &output, const Vec &target, Vec &costs) const |
| Computes the costs from already computed output. | |
| virtual TVec< std::string > | getTestCostNames () const |
| Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method). | |
| virtual TVec< std::string > | getTrainCostNames () const |
| Returns the names of the objective costs that the train method computes and for which it updates the VecStatsCollector train_stats. | |
| virtual string | classname () const |
| virtual OptionList & | getOptionList () const |
| virtual OptionMap & | getOptionMap () const |
| virtual RemoteMethodMap & | getRemoteMethodMap () const |
| virtual RankingFromKernel * | 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 PPath & | declaringFile () |
Public Attributes | |
| PP< Kernel > | logKernel |
| ### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //! | |
Static Public Attributes | |
| static StaticInitializer | _static_initializer_ |
Static Protected Member Functions | |
| static void | declareOptions (OptionList &ol) |
| Declares the class options. | |
Protected Attributes | |
| Vec | x |
| Vec | target |
| Vec | log_act |
| Vec | log_inact |
Private Types | |
| typedef PLearner | inherited |
Private Member Functions | |
| void | build_ () |
| This does the actual building. | |
The first sentence should be a BRIEF DESCRIPTION of what the class does.
Place the rest of the class programmer documentation here. Doxygen supports Javadoc-style comments. See http://www.doxygen.org/manual.html
Definition at line 62 of file RankingFromKernel.h.
typedef PLearner PLearn::RankingFromKernel::inherited [private] |
Reimplemented from PLearn::PLearner.
Definition at line 64 of file RankingFromKernel.h.
| PLearn::RankingFromKernel::RankingFromKernel | ( | ) |
Default constructor.
Definition at line 55 of file RankingFromKernel.cc.
{
// ...
// ### You may (or not) want to call build_() to finish building the object
// ### (doing so assumes the parent classes' build_() have been called too
// ### in the parent classes' constructors, something that you must ensure)
}
| string PLearn::RankingFromKernel::_classname_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 53 of file RankingFromKernel.cc.
| OptionList & PLearn::RankingFromKernel::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 53 of file RankingFromKernel.cc.
| RemoteMethodMap & PLearn::RankingFromKernel::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 53 of file RankingFromKernel.cc.
Reimplemented from PLearn::PLearner.
Definition at line 53 of file RankingFromKernel.cc.
| Object * PLearn::RankingFromKernel::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 53 of file RankingFromKernel.cc.
| StaticInitializer RankingFromKernel::_static_initializer_ & PLearn::RankingFromKernel::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 53 of file RankingFromKernel.cc.
| void PLearn::RankingFromKernel::build | ( | ) | [virtual] |
Finish building the object; just call inherited::build followed by build_()
Reimplemented from PLearn::PLearner.
Definition at line 93 of file RankingFromKernel.cc.
{
inherited::build();
build_();
}
| void PLearn::RankingFromKernel::build_ | ( | ) | [private] |
This does the actual building.
Reimplemented from PLearn::PLearner.
Definition at line 81 of file RankingFromKernel.cc.
{
// ### 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.
}
| string PLearn::RankingFromKernel::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file RankingFromKernel.cc.
| void PLearn::RankingFromKernel::computeCostsFromOutputs | ( | const Vec & | input, |
| const Vec & | output, | ||
| const Vec & | target, | ||
| Vec & | costs | ||
| ) | const [virtual] |
Computes the costs from already computed output.
Implements PLearn::PLearner.
Definition at line 196 of file RankingFromKernel.cc.
References PLearn::fast_exact_is_equal(), and PLearn::TVec< T >::resize().
{
costs.resize(nTestCosts());
if(fast_exact_is_equal(target[0],1))
costs[0] = output[0];
else
costs[0] = -output[0];
}

Computes the output from the input.
Reimplemented from PLearn::PLearner.
Definition at line 171 of file RankingFromKernel.cc.
References PLearn::exp(), PLearn::fast_exact_is_equal(), i, PLearn::logadd(), PLearn::TVec< T >::resize(), and x.
{
// Compute the output from the input.
// int nout = outputsize();
// output.resize(nout);
// ...
int i;
real log_k,log_result, weight;
log_act.resize(0);
log_inact.resize(0);
for (i=0; i < train_set->length();i++){
train_set->getExample(i,x, target, weight);
log_k = logKernel->evaluate(input,x);
if ( fast_exact_is_equal(target[0],1)) {
log_act.append(log_k);
}else{
log_inact.append(log_k);
}
}
log_result = logadd(log_act) - logadd(log_inact);
output.resize(1);
output[0] = exp(log_result);
}

| void PLearn::RankingFromKernel::declareOptions | ( | OptionList & | ol | ) | [static, protected] |
Declares the class options.
Reimplemented from PLearn::PLearner.
Definition at line 65 of file RankingFromKernel.cc.
References PLearn::OptionBase::buildoption, PLearn::declareOption(), and logKernel.
{
// ### 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
// ### ex:
declareOption(ol, "logKernel", &RankingFromKernel::logKernel, OptionBase::buildoption,
"A kernel taking an input and returning the log of its result.");
// Now call the parent class' declareOptions
inherited::declareOptions(ol);
}

| static const PPath& PLearn::RankingFromKernel::declaringFile | ( | ) | [inline, static] |
| RankingFromKernel * PLearn::RankingFromKernel::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::PLearner.
Definition at line 53 of file RankingFromKernel.cc.
| void PLearn::RankingFromKernel::forget | ( | ) | [virtual] |
(Re-)initializes the PLearner in its fresh state (that state may depend on the 'seed' option) and sets 'stage' back to 0 (this is the stage of a fresh learner!).
(Re-)initialize the PLearner in its fresh state (that state may depend on the 'seed' option) And sets 'stage' back to 0 (this is the stage of a fresh learner!)
A typical forget() method should do the following:
Reimplemented from PLearn::PLearner.
Definition at line 122 of file RankingFromKernel.cc.
{
}
| OptionList & PLearn::RankingFromKernel::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file RankingFromKernel.cc.
| OptionMap & PLearn::RankingFromKernel::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file RankingFromKernel.cc.
| RemoteMethodMap & PLearn::RankingFromKernel::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file RankingFromKernel.cc.
| TVec< string > PLearn::RankingFromKernel::getTestCostNames | ( | ) | const [virtual] |
Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method).
Implements PLearn::PLearner.
Definition at line 206 of file RankingFromKernel.cc.
References PLearn::TVec< T >::append(), and PLearn::TVec< T >::isEmpty().
{
static TVec<string> cost;
if (cost.isEmpty())
cost.append("lift_output");
return cost;
}

| TVec< string > PLearn::RankingFromKernel::getTrainCostNames | ( | ) | const [virtual] |
Returns 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 214 of file RankingFromKernel.cc.
References PLearn::TVec< T >::resize().
{
// Return the names of the objective costs that the train method computes and
// for which it updates the VecStatsCollector train_stats
// (these may or may not be exactly the same as what's returned by getTestCostNames).
// ...
static TVec<string> costs;
costs.resize(0);
return costs;
}

| void PLearn::RankingFromKernel::makeDeepCopyFromShallowCopy | ( | CopiesMap & | copies | ) | [virtual] |
Transforms a shallow copy into a deep copy.
Reimplemented from PLearn::PLearner.
Definition at line 100 of file RankingFromKernel.cc.
References 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("RankingFromKernel::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
}
| int PLearn::RankingFromKernel::outputsize | ( | ) | const [virtual] |
Returns the size of this learner's output, (which typically may depend on its inputsize(), targetsize() and set options).
Implements PLearn::PLearner.
Definition at line 115 of file RankingFromKernel.cc.
{
// Compute and return the size of this learner's output (which typically
// may depend on its inputsize(), targetsize() and set options).
return 1;
}
| void PLearn::RankingFromKernel::train | ( | ) | [virtual] |
The role of the train method is to bring the learner up to stage==nstages, updating the train_stats collector with training costs measured on-line in the process.
Implements PLearn::PLearner.
Definition at line 134 of file RankingFromKernel.cc.
References PLERROR, and PLWARNING.
{
// The role of the train method is to bring the learner up to stage==nstages,
// updating train_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
// This generic PLearner method does a number of standard stuff useful for
// (almost) any learner, and return 'false' if no training should take
// place. See PLearner.h for more details.
if (!initTrain())
return;
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
}
*/
if (train_set->targetsize() != 1) PLERROR("This PLearner is not built for multi-target problems");
PLWARNING("Train not implemented");
}
Reimplemented from PLearn::PLearner.
Definition at line 141 of file RankingFromKernel.h.
Vec PLearn::RankingFromKernel::log_act [mutable, protected] |
Definition at line 156 of file RankingFromKernel.h.
Vec PLearn::RankingFromKernel::log_inact [mutable, protected] |
Definition at line 156 of file RankingFromKernel.h.
### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //!
A kernel taking an input and returning the log of it's result.
Definition at line 73 of file RankingFromKernel.h.
Referenced by declareOptions().
Vec PLearn::RankingFromKernel::target [mutable, protected] |
Definition at line 152 of file RankingFromKernel.h.
Vec PLearn::RankingFromKernel::x [mutable, protected] |
Definition at line 152 of file RankingFromKernel.h.
1.7.4