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 3.7)
For further options, click the 'More' - button in the dialog.
All weka dialogs have a panel where you can specify classifier-specific parameters.
- Type: Data Training data
- Type: Weka 3.7 Classifier Trained model
Analytics > Mining > Weka > Weka (3.7) > Classification Algorithms > bayes
Make sure to have this extension installed:
KNIME Weka Data Mining Integration (3.7)
Update site for KNIME Analytics Platform 3.7:
KNIME Analytics Platform 3.7 Update Site