A Learner that returns the majority class, disregarding the example's attributes
Signal Classifier
sends data only if the learning data (signal Classified Examples
is present.
This widget provides a graphical interface to a learner which produces a classifier that always returns the majority class. When asked for probabilities, it will return the relative frequencies of the classes in the training set. When there are two or more majority classes, the classifier chooses the predicted class at random, but it will always return the same class for a particular example.
The widget is typically used to compare other learning algorithms with the default classification accuracy.
As all other widgets for classification, this one provides a learner and classifier, the former can be fed into widgets for testing learners, while the classifier itself is, well, not very useful.
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The only option is the name under which it will appear in, say, |
In a typical use of this widget, you would connect it to Test Learners to compare the scores of other learning algorithms (such as kNN, in this schema) with the default scores.