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

Class represents a simple clustering algorithm based on the selforganized feature map. More...
Public Member Functions  
def  __init__ (self, data, amount_clusters, epouch=100, ccore=True, **kwargs) 
Creates SOMSC (Self Organized Map for Simple Clustering) algorithm for clustering analysis. More...  
def  process (self) 
Performs cluster analysis by competition between neurons in selforganized map. More...  
def  predict (self, points) 
Calculates the closest cluster to each point. More...  
def  get_clusters (self) 
Returns list of allocated clusters, each cluster contains indexes of objects in list of data. More...  
def  get_cluster_encoding (self) 
Returns clustering result representation type that indicate how clusters are encoded. More...  
Class represents a simple clustering algorithm based on the selforganized feature map.
This algorithm uses amount of clusters that should be allocated as a size of SOM map. Captured objects by neurons are considered as clusters. The algorithm is designed to process data with Gaussian distribution that has spherical forms.
Example:
def pyclustering.cluster.somsc.somsc.__init__  (  self,  
data,  
amount_clusters,  
epouch = 100 , 

ccore = True , 

**  kwargs  
) 
Creates SOMSC (Self Organized Map for Simple Clustering) algorithm for clustering analysis.
[in]  data  (list): List of points that are used for processing. 
[in]  amount_clusters  (uint): Amount of clusters that should be allocated. 
[in]  epouch  (uint): Number of epochs for training of SOM. 
[in]  ccore  (bool): If it is True then CCORE implementation will be used for clustering analysis. 
[in]  **kwargs  Arbitrary keyword arguments (available arguments: random_state ). 
Keyword Args:
None
, current system time is used). def pyclustering.cluster.somsc.somsc.get_cluster_encoding  (  self  ) 
Returns clustering result representation type that indicate how clusters are encoded.
def pyclustering.cluster.somsc.somsc.get_clusters  (  self  ) 
Returns list of allocated clusters, each cluster contains indexes of objects in list of data.
Definition at line 121 of file somsc.py.
Referenced by pyclustering.samples.answer_reader.get_cluster_lengths().
def pyclustering.cluster.somsc.somsc.predict  (  self,  
points  
) 
Calculates the closest cluster to each point.
[in]  points  (array_like): Points for which closest clusters are calculated. 
def pyclustering.cluster.somsc.somsc.process  (  self  ) 
Performs cluster analysis by competition between neurons in selforganized map.