mlpack Namespace Reference

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

Namespaces

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

 

Functions

void CheckMatrices (const arma::mat &x, const arma::mat &xmlX, const arma::mat &jsonX, const arma::mat &binaryX)
 
void CheckMatrices (const arma::Mat< size_t > &x, const arma::Mat< size_t > &xmlX, const arma::Mat< size_t > &jsonX, const arma::Mat< size_t > &binaryX)
 
void CheckMatrices (const arma::cube &x, const arma::cube &xmlX, const arma::cube &jsonX, const arma::cube &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 &jsonT, 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 *&jsonT, 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 mlpack::CheckMatrices ( const arma::mat &  x,
const arma::mat &  xmlX,
const arma::mat &  jsonX,
const arma::mat &  binaryX 
)

◆ CheckMatrices() [2/3]

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

◆ CheckMatrices() [3/3]

void mlpack::CheckMatrices ( const arma::cube &  x,
const arma::cube &  xmlX,
const arma::cube &  jsonX,
const arma::cube &  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 mlpack::SerializeObject ( T &  t,
T &  newT 
)

Definition at line 145 of file serialization.hpp.

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

Referenced by SerializeObjectAll().

◆ SerializeObjectAll()

void mlpack::SerializeObjectAll ( T &  t,
T &  xmlT,
T &  jsonT,
T &  binaryT 
)

Definition at line 172 of file serialization.hpp.

References SerializeObject().

◆ SerializePointerObject()

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

Definition at line 184 of file serialization.hpp.

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

Referenced by SerializePointerObjectAll().

◆ SerializePointerObjectAll()

void mlpack::SerializePointerObjectAll ( T *  t,
T *&  xmlT,
T *&  jsonT,
T *&  binaryT 
)

Definition at line 206 of file serialization.hpp.

References CheckMatrices(), and SerializePointerObject().

◆ TestAllArmadilloSerialization() [1/2]

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

Definition at line 78 of file serialization.hpp.

References TestArmadilloSerialization().

◆ TestAllArmadilloSerialization() [2/2]

void mlpack::TestAllArmadilloSerialization ( MatType &  x)

Definition at line 132 of file serialization.hpp.

References TestArmadilloSerialization().

◆ TestArmadilloSerialization() [1/2]

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

Definition at line 26 of file serialization.hpp.

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

Referenced by TestAllArmadilloSerialization().

◆ TestArmadilloSerialization() [2/2]

void mlpack::TestArmadilloSerialization ( MatType &  x)

Definition at line 92 of file serialization.hpp.

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