Probabilistic Topological Map and Binary data
Lebbah, Moustapha ; Chabanon, C. ; Thiria, Sylvie ; Badran, Fouad
HAL, hal-01124637 / Harvested from HAL
Text on HAL
The Self Organizing Map (SOM) proposed by Kohonen is a well known neuralmodel which provides both quantization and clustering of the observationspace. In this paper, we adapt the Bernoulli mixture approach to the model of binary topological map and show that using aprobabilistic formalism gives rise to better quantization process andclassification performances.
Publié le : 2001-01-01
Classification:  [INFO]Computer Science [cs],  [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] 
@article{hal-01124637,
     author = {Lebbah, Moustapha and Chabanon, C. and Thiria, Sylvie and Badran, Fouad},
     title = {Probabilistic Topological Map and Binary data},
     journal = {HAL},
     volume = {2001},
     number = {0},
     year = {2001},
     language = {en},
     url = {http://dml.mathdoc.fr/item/hal-01124637}
}

Lebbah, Moustapha; Chabanon, C.; Thiria, Sylvie; Badran, Fouad. Probabilistic Topological Map and Binary data. HAL, Tome 2001 (2001) no. 0, . http://gdmltest.u-ga.fr/item/hal-01124637/