A Binary Approximate Naive Bayesian Classification Algorithm Based on SOM Neural Network Clustering

Although the classification performance of Naive Bayesian algorithm is relatively good, the time complexity and spatial complexity of the algorithm are linearly increasing with the increase of data volume. In order to reduce the complexity of Naive Bayesian algorithm, a two - point approach naive Ba...

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Veröffentlicht in:	2017 International Conference on Computer Systems, Electronics and Control (ICCSEC) S. 1344 - 1347
Hauptverfasser:	Honghong, Shen, Lili, He
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2017
Schlagworte:	Approximation algorithms Bayes methods Classification algorithms Clustering algorithms Complexity theory dichotomous approximation naive Bayesian algorithm Neural networks Neurons SOM neural network clustering
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