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This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

Node Classification

This module provides the functions for node classification problem.

The functions in this module are not imported into the top level networkx namespace. You can access these functions by importing the networkx.algorithms.node_classification modules, then accessing the functions as attributes of node_classification. For example:

>>> import networkx as nx
>>> from networkx.algorithms import node_classification
>>> G = nx.path_graph(4)
>>> G.edges()
EdgeView([(0, 1), (1, 2), (2, 3)])
>>> G.node[0]['label'] = 'A'
>>> G.node[3]['label'] = 'B'
>>> node_classification.harmonic_function(G)  # doctest: +SKIP
['A', 'A', 'B', 'B']

Harmonic Function

Function for computing Harmonic function algorithm by Zhu et al.

References

Zhu, X., Ghahramani, Z., & Lafferty, J. (2003, August). Semi-supervised learning using gaussian fields and harmonic functions. In ICML (Vol. 3, pp. 912-919).

harmonic_function(G[, max_iter, label_name])

Node classification by Harmonic function

Local and Global Consistency

Function for computing Local and global consistency algorithm by Zhou et al.

References

Zhou, D., Bousquet, O., Lal, T. N., Weston, J., & Schölkopf, B. (2004). Learning with local and global consistency. Advances in neural information processing systems, 16(16), 321-328.

local_and_global_consistency(G[, alpha, …])

Node classification by Local and Global Consistency