Majority

A learner that returns a majority class in a data set for all instances.

Signals

Inputs:

• Data

  A data set

• Preprocessor

  Preprocessed data

Outputs:

• Learner

  A majority learning algorithm

• Classifier

  A trained classifier. In the output only if the learning data (signal Data) is present.

Description

This learner produces a classifier that always predicts 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 randomly, but always returns the same class for a particular example.

The widget is typically used to compare other learning algorithms with the default classification accuracy.

This widget provides the user with two options:

1. The name under which it will appear in other widgets (the default name is “Majority”).
2. Producing a report.

If you change the widget’s name, you need to click Apply. Alternatively, tick the box on the left side and changes will be communicated automatically.

Example

In a typical use of this widget, it would be connected to Test&Score to compare the scores of other learning algorithms (such as kNN) with the default scores.