PLearn 0.1
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#include <plearn_learners/generic/PLearner.h>
#include <plearn_learners/testers/PTester.h>
#include <plearn/vmat/FileVMatrix.h>
#include <plearn/vmat/MemoryVMatrix.h>
#include <plearn/io/load_and_save.h>
#include <plearn/io/fileutils.h>
#include <plearn/math/random.h>
#include <plearn/vmat/ExplicitSplitter.h>
#include <plearn_learners/nearest_neighbors/BallTreeNearestNeighbors.h>
#include <plearn_learners/second_iteration/CovariancePreservationImputationVMatrix.h>
#include <plearn_learners/second_iteration/NeighborhoodImputationVMatrix.h>
#include <plearn_learners/second_iteration/Experimentation.h>
Go to the source code of this file.
Classes | |
class | PLearn::NeighborhoodConditionalMean |
Generate samples from a mixture of two gaussians. More... | |
class | PLearn::DiffTemplate< ObjectType, NeighborhoodConditionalMean > |
class | PLearn::TypeTraits< NeighborhoodConditionalMean > |
Namespaces | |
namespace | PLearn |
< for swap | |
Functions | |
Object * | PLearn::toObjectPtr (const NeighborhoodConditionalMean &o) |
PStream & | PLearn::operator>> (PStream &in, NeighborhoodConditionalMean &o) |
PStream & | PLearn::operator>> (PStream &in, NeighborhoodConditionalMean *&o) |
PStream & | PLearn::operator<< (PStream &out, const NeighborhoodConditionalMean &o) |
PStream & | PLearn::operator>> (PStream &in, PP< NeighborhoodConditionalMean > &o) |
template<class ObjectType > | |
int | PLearn::diff (const string &refer, const string &other, const Option< ObjectType, NeighborhoodConditionalMean > *opt, PLearnDiff *diffs) |
Definition in file NeighborhoodConditionalMean.h.