ensmallen
mlpack
fast, flexible C++ machine learning library
mlpack::kde Namespace Reference

Kernel Density Estimation. More...

Classes

class  AbsErrorVisitor
 AbsErrorVisitor modifies absolute error tolerance for a KDEType. More...

 
class  BandwidthVisitor
 BandwidthVisitor modifies the bandwidth of a KDEType kernel. More...

 
class  DeleteVisitor
 
class  DualBiKDE
 DualBiKDE computes a Kernel Density Estimation on the given KDEType. More...

 
class  DualMonoKDE
 DualMonoKDE computes a Kernel Density Estimation on the given KDEType. More...

 
class  KDE
 The KDE class is a template class for performing Kernel Density Estimations. More...

 
class  KDECleanRules
 A dual-tree traversal Rules class for cleaning used trees before performing kernel density estimation. More...

 
struct  KDEDefaultParams
 KDEDefaultParams contains the default input parameter values for KDE. More...

 
class  KDEModel
 
class  KDERules
 A dual-tree traversal Rules class for kernel density estimation. More...

 
class  KDEStat
 Extra data for each node in the tree for the task of kernel density estimation. More...

 
class  KernelNormalizer
 KernelNormalizer holds a set of methods to normalize estimations applying in each case the appropiate kernel normalizer function. More...

 
class  MCBreakCoefVisitor
 MCBreakCoefVisitor sets the Monte Carlo break coefficient. More...

 
class  MCEntryCoefVisitor
 MCEntryCoefVisitor sets the Monte Carlo entry coefficient. More...

 
class  MCProbabilityVisitor
 MCProbabilityVisitor sets the Monte Carlo probability for a given KDEType. More...

 
class  MCSampleSizeVisitor
 MCSampleSizeVisitor sets the Monte Carlo intial sample size for a given KDEType. More...

 
class  ModeVisitor
 ModeVisitor exposes the Mode() method of the KDEType. More...

 
class  MonteCarloVisitor
 MonteCarloVisitor activates or deactivates Monte Carlo for a given KDEType. More...

 
class  RelErrorVisitor
 RelErrorVisitor modifies relative error tolerance for a KDEType. More...

 
class  TrainVisitor
 TrainVisitor trains a given KDEType using a reference set. More...

 

Typedefs

template
<
typename
KernelType
,
template
<
typename
TreeMetricType
,
typename
TreeStatType
,
typename
TreeMatType
>
class
TreeType
>
using KDEType = KDE< KernelType, metric::EuclideanDistance, arma::mat, TreeType, TreeType< metric::EuclideanDistance, kde::KDEStat, arma::mat >::template DualTreeTraverser, TreeType< metric::EuclideanDistance, kde::KDEStat, arma::mat >::template SingleTreeTraverser >
 Alias template. More...

 

Enumerations

enum  KDEMode
{
  DUAL_TREE_MODE
,
  SINGLE_TREE_MODE

}
 KDEMode represents the ways in which KDE algorithm can be executed. More...

 

Detailed Description

Kernel Density Estimation.

Typedef Documentation

◆ KDEType

using KDEType = KDE<KernelType, metric::EuclideanDistance, arma::mat, TreeType, TreeType<metric::EuclideanDistance, kde::KDEStat, arma::mat>::template DualTreeTraverser, TreeType<metric::EuclideanDistance, kde::KDEStat, arma::mat>::template SingleTreeTraverser>

Alias template.

Definition at line 45 of file kde_model.hpp.

Enumeration Type Documentation

◆ KDEMode

enum KDEMode

KDEMode represents the ways in which KDE algorithm can be executed.

Enumerator
DUAL_TREE_MODE 
SINGLE_TREE_MODE 

Definition at line 25 of file kde.hpp.