Class represents clustering algorithm CLARANS (a method for clustering objects for spatial data mining). More...
Public Member Functions | |
def | __init__ (self, data, number_clusters, numlocal, maxneighbor) |
Constructor of clustering algorithm CLARANS. More... | |
def | process (self) |
Performs cluster analysis in line with rules of CLARANS algorithm. More... | |
def | get_clusters (self) |
Returns allocated clusters by the algorithm. More... | |
def | get_medoids (self) |
Returns list of medoids of allocated clusters. More... | |
def | get_cluster_encoding (self) |
Returns clustering result representation type that indicate how clusters are encoded. More... | |
Class represents clustering algorithm CLARANS (a method for clustering objects for spatial data mining).
Definition at line 35 of file clarans.py.
def pyclustering.cluster.clarans.clarans.__init__ | ( | self, | |
data, | |||
number_clusters, | |||
numlocal, | |||
maxneighbor | |||
) |
Constructor of clustering algorithm CLARANS.
The higher the value of maxneighbor, the closer is CLARANS to K-Medoids, and the longer is each search of a local minima.
[in] | data | (list): Input data that is presented as list of points (objects), each point should be represented by list or tuple. |
[in] | number_clusters | (uint): amount of clusters that should be allocated. |
[in] | numlocal | (uint): the number of local minima obtained (amount of iterations for solving the problem). |
[in] | maxneighbor | (uint): the maximum number of neighbors examined. |
Definition at line 41 of file clarans.py.
def pyclustering.cluster.clarans.clarans.get_cluster_encoding | ( | self | ) |
Returns clustering result representation type that indicate how clusters are encoded.
Definition at line 124 of file clarans.py.
def pyclustering.cluster.clarans.clarans.get_clusters | ( | self | ) |
Returns allocated clusters by the algorithm.
Definition at line 96 of file clarans.py.
Referenced by pyclustering.samples.answer_reader.get_cluster_lengths(), and pyclustering.cluster.optics.optics.process().
def pyclustering.cluster.clarans.clarans.get_medoids | ( | self | ) |
Returns list of medoids of allocated clusters.
Definition at line 112 of file clarans.py.
def pyclustering.cluster.clarans.clarans.process | ( | self | ) |
Performs cluster analysis in line with rules of CLARANS algorithm.
Definition at line 66 of file clarans.py.