pyclustering
0.10.1
pyclustring is a Python, C++ data mining library.

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 20 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 KMedoids, 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 26 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 134 of file clarans.py.
def pyclustering.cluster.clarans.clarans.get_clusters  (  self  ) 
Returns allocated clusters by the algorithm.
Definition at line 106 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 122 of file clarans.py.
def pyclustering.cluster.clarans.clarans.process  (  self  ) 
Performs cluster analysis in line with rules of CLARANS algorithm.
Definition at line 73 of file clarans.py.