Naive Bayes
Naive Bayesian Learner
Signals
Inputs:
- Data
Data set
- Preprocessor
Preprocessed data
Outputs:
- Learner
Naive Bayesian learning algorithm with settings as specified in the dialog. It can be fed into widgets for testing learners.
- Naive Bayesian Classifier
Trained classifier (a subtype of Classifier). The Naive Bayesian Classifier signal sends data only if the learning data (signal Data) is present.
Description
The only option in this widget is the name under which it will appear in other widgets. The default name is 'Naive Bayes'. When you change it, you need to press 'Apply'.
Examples
Here we present two uses of this widget. First we compare the results of Naive Bayesian learner with another learner, a Random Forest.
The second schema show the quality of predictions made with Naive Bayes. We feed the Test Learners widget a Naive Bayes learner and then send the data to the Confusion Matrix. In this widget we select misclassified instances and show them in Scatterplot. The bold dots in the scatterplot are the misclassified instances from Naive Bayes.