Represents SOM parameters. More...

Public Member Functions
def	__init__ (self)
	Creates SOM parameters.

Public Attributes
	init_type
	Defines an initialization way for neuron weights (random, random in center of the input data, random distributed in data, ditributed in line with uniform grid). More...

	init_radius
	Initial radius. More...

	init_learn_rate
	Rate of learning. More...

	adaptation_threshold
	Condition that defines when the learining process should be stopped. More...

	random_state
	Seed for random state (by default is `None`, current system time is used). More...

Detailed Description

Represents SOM parameters.

Definition at line 89 of file som.py.

Member Data Documentation

◆ adaptation_threshold

pyclustering.nnet.som.som_parameters.adaptation_threshold

Condition that defines when the learining process should be stopped.

It is used when the autostop mode is on.

Definition at line 111 of file som.py.

◆ init_learn_rate

pyclustering.nnet.som.som_parameters.init_learn_rate

Rate of learning.

Definition at line 108 of file som.py.

◆ init_radius

pyclustering.nnet.som.som_parameters.init_radius

Initial radius.

If the initial radius is not specified (equals to None) then it will be calculated by SOM.

Definition at line 105 of file som.py.

◆ init_type

pyclustering.nnet.som.som_parameters.init_type

Defines an initialization way for neuron weights (random, random in center of the input data, random distributed in data, ditributed in line with uniform grid).

Definition at line 102 of file som.py.

◆ random_state

pyclustering.nnet.som.som_parameters.random_state

Seed for random state (by default is None, current system time is used).

Definition at line 114 of file som.py.

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

pyclustering/nnet/som.py

Public Member Functions