mlpack 3.4.2
Namespaces | Classes | Functions
mlpack Namespace Reference

Linear algebra utility functions, generally performed on matrices or vectors. More...

Namespaces

namespace  adaboost
 
namespace  amf
 Alternating Matrix Factorization.
 
namespace  ann
 Artificial Neural Network.
 
namespace  bindings
 
namespace  bound
 
namespace  cf
 Collaborative filtering.
 
namespace  cv
 
namespace  data
 Functions to load and save matrices and models.
 
namespace  dbscan
 
namespace  decision_stump
 
namespace  det
 Density Estimation Trees.
 
namespace  distribution
 Probability distributions.
 
namespace  emst
 Euclidean Minimum Spanning Trees.
 
namespace  fastmks
 Fast max-kernel search.
 
namespace  gmm
 Gaussian Mixture Models.
 
namespace  hmm
 Hidden Markov Models.
 
namespace  hpt
 
namespace  kde
 Kernel Density Estimation.
 
namespace  kernel
 Kernel functions.
 
namespace  kmeans
 K-Means clustering.
 
namespace  kpca
 
namespace  lcc
 
namespace  lmnn
 Large Margin Nearest Neighbor.
 
namespace  math
 Miscellaneous math routines.
 
namespace  matrix_completion
 
namespace  meanshift
 Mean shift clustering.
 
namespace  metric
 
namespace  mvu
 
namespace  naive_bayes
 The Naive Bayes Classifier.
 
namespace  nca
 Neighborhood Components Analysis.
 
namespace  neighbor
 
namespace  nn
 
namespace  pca
 
namespace  perceptron
 
namespace  radical
 
namespace  range
 Range-search routines.
 
namespace  regression
 Regression methods.
 
namespace  rl
 
namespace  sfinae
 
namespace  sparse_coding
 
namespace  svd
 
namespace  svm
 
namespace  tree
 Trees and tree-building procedures.
 
namespace  util
 

Classes

class  Backtrace
 Provides a backtrace. More...
 
class  IO
 Parses the command line for parameters and holds user-specified parameters. More...
 
class  Log
 Provides a convenient way to give formatted output. More...
 
class  Timer
 The timer class provides a way for mlpack methods to be timed. More...
 
class  Timers
 

Functions

void CheckMatrices (const arma::cube &x, const arma::cube &xmlX, const arma::cube &textX, const arma::cube &binaryX)
 
void CheckMatrices (const arma::mat &x, const arma::mat &xmlX, const arma::mat &textX, const arma::mat &binaryX)
 
void CheckMatrices (const arma::Mat< size_t > &x, const arma::Mat< size_t > &xmlX, const arma::Mat< size_t > &textX, const arma::Mat< size_t > &binaryX)
 
template<typename T >
T::elem_type * GetMemory (T &m)
 Return the matrix's allocated memory pointer, unless the matrix is using its internal preallocated memory, in which case we copy that and return a pointer to the memory we just made. More...
 
template<typename T , typename IArchiveType , typename OArchiveType >
void SerializeObject (T &t, T &newT)
 
template<typename T >
void SerializeObjectAll (T &t, T &xmlT, T &textT, T &binaryT)
 
template<typename T , typename IArchiveType , typename OArchiveType >
void SerializePointerObject (T *t, T *&newT)
 
template<typename T >
void SerializePointerObjectAll (T *t, T *&xmlT, T *&textT, T *&binaryT)
 
template<typename CubeType >
void TestAllArmadilloSerialization (arma::Cube< CubeType > &x)
 
template<typename MatType >
void TestAllArmadilloSerialization (MatType &x)
 
template<typename CubeType , typename IArchiveType , typename OArchiveType >
void TestArmadilloSerialization (arma::Cube< CubeType > &x)
 
template<typename MatType , typename IArchiveType , typename OArchiveType >
void TestArmadilloSerialization (MatType &x)
 

Detailed Description

Linear algebra utility functions, generally performed on matrices or vectors.

This class is used to update the weightVectors matrix according to the simple update rule as discussed by Rosenblatt:

if a vector x has been incorrectly classified by a weight w, then w = w - x and w'= w'+ x

where w' is the weight vector which correctly classifies x.

Function Documentation

◆ CheckMatrices() [1/3]

void CheckMatrices ( const arma::cube &  x,
const arma::cube &  xmlX,
const arma::cube &  textX,
const arma::cube &  binaryX 
)

◆ CheckMatrices() [2/3]

void CheckMatrices ( const arma::mat &  x,
const arma::mat &  xmlX,
const arma::mat &  textX,
const arma::mat &  binaryX 
)

◆ CheckMatrices() [3/3]

void CheckMatrices ( const arma::Mat< size_t > &  x,
const arma::Mat< size_t > &  xmlX,
const arma::Mat< size_t > &  textX,
const arma::Mat< size_t > &  binaryX 
)

◆ GetMemory()

T::elem_type * mlpack::GetMemory ( T &  m)
inline

Return the matrix's allocated memory pointer, unless the matrix is using its internal preallocated memory, in which case we copy that and return a pointer to the memory we just made.

Definition at line 27 of file arma_util.hpp.

◆ SerializeObject()

void SerializeObject ( T &  t,
T &  newT 
)

◆ SerializeObjectAll()

void SerializeObjectAll ( T &  t,
T &  xmlT,
T &  textT,
T &  binaryT 
)

Definition at line 240 of file serialization.hpp.

References SerializeObject().

◆ SerializePointerObject()

void SerializePointerObject ( T *  t,
T *&  newT 
)

Definition at line 252 of file serialization.hpp.

References mlpack::data::binary, FilterFileName(), and MLPACK_COUT_STREAM.

Referenced by SerializePointerObjectAll().

◆ SerializePointerObjectAll()

void SerializePointerObjectAll ( T *  t,
T *&  xmlT,
T *&  textT,
T *&  binaryT 
)

Definition at line 297 of file serialization.hpp.

References SerializePointerObject().

◆ TestAllArmadilloSerialization() [1/2]

void TestAllArmadilloSerialization ( arma::Cube< CubeType > &  x)

Definition at line 106 of file serialization.hpp.

References TestArmadilloSerialization().

◆ TestAllArmadilloSerialization() [2/2]

void TestAllArmadilloSerialization ( MatType &  x)

Definition at line 180 of file serialization.hpp.

References TestArmadilloSerialization().

◆ TestArmadilloSerialization() [1/2]

void TestArmadilloSerialization ( arma::Cube< CubeType > &  x)

Definition at line 33 of file serialization.hpp.

References mlpack::data::binary, and FilterFileName().

Referenced by TestAllArmadilloSerialization().

◆ TestArmadilloSerialization() [2/2]

void TestArmadilloSerialization ( MatType &  x)

Definition at line 120 of file serialization.hpp.

References mlpack::data::binary, and FilterFileName().