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k-means.hpp File Reference
#include <thrill/api/all_gather.hpp>
#include <thrill/api/cache.hpp>
#include <thrill/api/collapse.hpp>
#include <thrill/api/reduce_by_key.hpp>
#include <thrill/api/sample.hpp>
#include <thrill/api/sum.hpp>
#include <thrill/common/vector.hpp>
#include <cereal/types/vector.hpp>
#include <thrill/data/serialization_cereal.hpp>
#include <limits>
#include <string>
#include <utility>
#include <vector>
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Classes

struct  CentroidAccumulated< Point >
 A point which contains "count" accumulated vectors. More...
 
struct  ClosestCentroid< Point >
 Assignment of a point to a cluster, which is the input to. More...
 
class  KMeansModel< Point >
 Model returned by KMeans algorithm containing results. More...
 

Namespaces

 examples
 
 examples::k_means
 

Macros

#define THRILL_EXAMPLES_K_MEANS_K_MEANS_HEADER
 

Typedefs

template<size_t D>
using Point = thrill::common::Vector< D, double >
 Compile-Time Fixed-Dimensional Points. More...
 
template<typename Point >
using PointClusterId = std::pair< Point, size_t >
 
using VPoint = thrill::common::VVector< double >
 A variable D-dimensional point with double precision. More...
 

Functions

template<typename Point , typename InStack >
auto KMeans (const DIA< Point, InStack > &input_points, size_t dimensions, size_t num_clusters, size_t iterations)
 

Macro Definition Documentation

#define THRILL_EXAMPLES_K_MEANS_K_MEANS_HEADER

Definition at line 14 of file k-means.hpp.