Concept information
Preferred term
majority classifier
Definition
- A classifier where every point is assigned to whichever class is in the majority in the training set. If there is no majority one of the classes is chosen arbitrarily. This classifier is often used as a baseline for comparing other machine learning techniques. (Carleton College)
Broader concept
Example
- In fact the majority classifier is only slightly outperformed by other classifiers if we look at this evaluation measure. (Zubiaga, Kochkina, Liakata, Procter & Lukasik, 2016)
- In that case the majority classifier does not know which sense to assign whereupon we apply a preprocess named unknown connective substitution to find a clue for the classifier. (Kido & Aizawa, 2016)
- The majority classifier always predicts the most common opinion of all users for which the opinion to be predicted is known (PoC) or considers the averaged weight (PoW and PoS). (Brenneis, Behrendt & Harmeling, 2021)
In other languages
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French
URI
http://data.loterre.fr/ark:/67375/8LP-CNL59CQ1-8
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