PLearn 0.1
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#include <plearn/vmat/ClassSubsetVMatrix.h>
#include <plearn_learners/generic/PLearner.h>
#include <plearn_learners/online/GradNNetLayerModule.h>
#include <plearn_learners/online/OnlineLearningModule.h>
#include <plearn_learners/online/CostModule.h>
#include <plearn_learners/online/ModuleStackModule.h>
#include <plearn_learners/online/NLLCostModule.h>
#include <plearn_learners/online/ClassErrorCostModule.h>
#include <plearn_learners/online/CombiningCostsModule.h>
#include <plearn_learners/online/RBMClassificationModule.h>
#include <plearn_learners/online/RBMLayer.h>
#include <plearn_learners/online/RBMMixedLayer.h>
#include <plearn_learners/online/RBMConnection.h>
#include <plearn_learners/online/SoftmaxModule.h>
#include <plearn/misc/PTimer.h>
Go to the source code of this file.
Classes | |
class | PLearn::TopDownAsymetricDeepNetwork |
Neural net, trained layer-wise in a greedy but focused fashion using autoassociators/RBMs and a supervised non-parametric gradient. More... | |
class | PLearn::DiffTemplate< ObjectType, TopDownAsymetricDeepNetwork > |
class | PLearn::TypeTraits< TopDownAsymetricDeepNetwork > |
Namespaces | |
namespace | PLearn |
< for swap | |
Functions | |
Object * | PLearn::toObjectPtr (const TopDownAsymetricDeepNetwork &o) |
PStream & | PLearn::operator>> (PStream &in, TopDownAsymetricDeepNetwork &o) |
PStream & | PLearn::operator>> (PStream &in, TopDownAsymetricDeepNetwork *&o) |
PStream & | PLearn::operator<< (PStream &out, const TopDownAsymetricDeepNetwork &o) |
PStream & | PLearn::operator>> (PStream &in, PP< TopDownAsymetricDeepNetwork > &o) |
template<class ObjectType > | |
int | PLearn::diff (const string &refer, const string &other, const Option< ObjectType, TopDownAsymetricDeepNetwork > *opt, PLearnDiff *diffs) |
Definition in file TopDownAsymetricDeepNetwork.h.