kmeans
k-means clustering in C++
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Interface for matrix data. More...
#include <Matrix.hpp>
Public Member Functions | |
virtual Index_ | num_observations () const =0 |
virtual std::size_t | num_dimensions () const =0 |
virtual std::unique_ptr< RandomAccessExtractor< Index_, Data_ > > | new_extractor () const =0 |
virtual std::unique_ptr< ConsecutiveAccessExtractor< Index_, Data_ > > | new_extractor (Index_ start, Index_ length) const =0 |
virtual std::unique_ptr< IndexedAccessExtractor< Index_, Data_ > > | new_extractor (const Index_ *sequence, std::size_t length) const =0 |
Interface for matrix data.
This defines the expectations for a matrix of observation-level data to be used in Initialize::run()
and Refine::run()
. Each matrix should support extraction of the vector of coordinates for each observation.
Index_ | Integer type of the observation indices. |
Data_ | Numeric type of the data. |
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pure virtual |
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pure virtual |
[in] | sequence | Pointer to an array of sorted and unique indices of observations, to be accessed in the provided order. It is assumed that the vector will not be deallocated before the destruction of the returned IndexedAccessWorkspace . |
length | Number of observations in sequence . |
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pure virtual |
start | Start of the contiguous block of observations to be accessed consecutively. |
length | Length of the contiguous block of observations to be accessed consecutively. |
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pure virtual |
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pure virtual |