Creates a set of pattern (each later representing a mode) which than are randomly perturbed to create the data set. The dataset was introduced in Desjardins et al. (2010) (Parallel Tempering for training restricted Boltzmann machines, AISTATS 2010) More...
#include <shark/Unsupervised/RBM/Problems/DistantModes.h>
Public Member Functions  
DistantModes (double p=0, unsigned dim=16, unsigned modes=4, unsigned copies=2500, size_t batchSize=0)  
UnlabeledData< RealVector >  data () const 
returns the generated dataset More...  
std::size_t  inputDimension () const 
returns the dimensionality of the data More...  
Creates a set of pattern (each later representing a mode) which than are randomly perturbed to create the data set. The dataset was introduced in Desjardins et al. (2010) (Parallel Tempering for training restricted Boltzmann machines, AISTATS 2010)
The higher the perturbation is the harder it is to classify, but the closer are the modes and thus the easier the data distribution is to learn.
Definition at line 45 of file DistantModes.h.

inline 
generates the DistantModes distribution.
p  the probability of changing a input neuron 
dim  the dimensionality of the data. 
modes  the number of modes, should be a multiple of 2 
copies  the number of disturbed copies for each mode 
batchSize  the size of the batches in which the generated data set is organized 
Definition at line 93 of file DistantModes.h.

inline 
returns the generated dataset
Definition at line 99 of file DistantModes.h.

inline 
returns the dimensionality of the data
Definition at line 104 of file DistantModes.h.