pyclustering.cluster.clarans.clarans Class Reference

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...

Detailed Description

Class represents clustering algorithm CLARANS (a method for clustering objects for spatial data mining).

Definition at line 20 of file clarans.py.

Constructor & Destructor Documentation

__init__()

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.

Parameters

[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.

Member Function Documentation

get_cluster_encoding()

def pyclustering.cluster.clarans.clarans.get_cluster_encoding

(

self

)

Returns clustering result representation type that indicate how clusters are encoded.

Returns

(type_encoding) Clustering result representation.

See also

get_clusters()

Definition at line 134 of file clarans.py.

get_clusters()

def pyclustering.cluster.clarans.clarans.get_clusters

(

self

)

Returns allocated clusters by the algorithm.

Remarks

Allocated clusters can be returned only after data processing (use method process()), otherwise empty list is returned.

Returns

(list) List of allocated clusters, each cluster contains indexes of objects in list of data.

See also

process()

get_medoids()

Definition at line 106 of file clarans.py.

Referenced by pyclustering.samples.answer_reader.get_cluster_lengths(), and pyclustering.cluster.optics.optics.process().

get_medoids()

def pyclustering.cluster.clarans.clarans.get_medoids

(

self

)

Returns list of medoids of allocated clusters.

See also

process()

get_clusters()

Definition at line 122 of file clarans.py.

process()

def pyclustering.cluster.clarans.clarans.process

(

self

)

Performs cluster analysis in line with rules of CLARANS algorithm.

Returns

(clarans) Returns itself (CLARANS instance).

See also

get_clusters()

get_medoids()

Definition at line 73 of file clarans.py.

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The documentation for this class was generated from the following file:

• pyclustering/cluster/clarans.py