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NaiveBayesMultinomial (3.6)

Analytics Integrations Weka Weka (3.6) Classification Algorithms
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Class for building and using a multinomial Naive Bayes classifier. For more information see, Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998. The core equation for this classifier: P[Ci|D] = (P[D|Ci] x P[Ci]) / P[D] (Bayes rule) where Ci is class i and D is a document.

(based on WEKA 3.6)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Node details

Input ports
  1. Type: Table
    Training data
    Training data
Output ports
  1. Type: Weka 3.6 Classifier
    Trained classifier
    Trained classifier

Extension

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