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/*!
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
*/
#pragma once
#include <memory>
#include <vector>
#include <pyclustering/cluster/cluster_data.hpp>
#include <pyclustering/definitions.hpp>
namespace pyclustering {
namespace clst {
/*!
@brief Container for membership (probability) of each point from data.
*/
using membership_sequence = dataset;
/*!
@class fcm_data fcm_data.hpp pyclustering/cluster/fcm_data.hpp
@brief Clustering results of Fuzzy C-Means algorithm that consists of information about allocated
clusters and centers of each cluster.
*/
class fcm_data : public cluster_data {
private:
dataset m_centers = { };
dataset m_membership = { };
public:
/*!
@brief Returns reference to centers of allocated clusters.
@return Reference to centers of allocated clusters.
*/
dataset & centers() { return m_centers; }
/*!
@brief Returns const reference to centers of allocated clusters.
@return Const reference to centers of allocated clusters.
*/
const dataset & centers() const { return m_centers; };
/*!
@brief Returns reference to cluster membership (probability) for each point in data.
@return Reference to cluster membership (probability) for each point in data.
*/
membership_sequence & membership() { return m_membership; }
/*!
@brief Returns constant reference to cluster membership (probability) for each point in data.
@return Constant reference to cluster membership (probability) for each point in data.
*/
const membership_sequence & membership() const { return m_membership; };
};
}
}
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