1#ifndef KMEANS_MATRIX_HPP 
    2#define KMEANS_MATRIX_HPP 
   26template<
typename Index_, 
typename Data_>
 
   60template<
typename Index_, 
typename Data_>
 
   96template<
typename Index_, 
typename Data_>
 
  132template<
typename Index_, 
typename Data_>
 
  163    virtual std::unique_ptr<RandomAccessExtractor<Index_, Data_> > 
new_extractor() 
const = 0;
 
  170    virtual std::unique_ptr<ConsecutiveAccessExtractor<Index_, Data_> > 
new_extractor(Index_ start, Index_ length) 
const = 0;
 
  178    virtual std::unique_ptr<IndexedAccessExtractor<Index_, Data_> > 
new_extractor(
const Index_* sequence, std::size_t length) 
const = 0;
 
 
  185template<
class Matrix_>
 
  186using Index = I<decltype(std::declval<Matrix_>().num_observations())>;
 
Interface for matrix data.
Definition Matrix.hpp:133
 
virtual std::unique_ptr< ConsecutiveAccessExtractor< Index_, Data_ > > new_extractor(Index_ start, Index_ length) const =0
 
virtual std::size_t num_dimensions() const =0
 
virtual std::unique_ptr< RandomAccessExtractor< Index_, Data_ > > new_extractor() const =0
 
virtual Index_ num_observations() const =0
 
virtual std::unique_ptr< IndexedAccessExtractor< Index_, Data_ > > new_extractor(const Index_ *sequence, std::size_t length) const =0
 
Extractor for accessing random observations.
Definition Matrix.hpp:27
 
virtual const Data_ * get_observation(Index_ i)=0
 
Perform k-means clustering.
Definition compute_wcss.hpp:16