Category biases arise from learning sets but not from choice sets

The Generalized Context Model (GCM) classifies items based on similarity to category exemplars. The model can include category-specific biases. Without these bias parameters, the GCM satisfies the independence of irrelevant alternatives (IIA) principle from the decision-making literature, in which the relative preference of two options does not change upon the introduction of a third option. In two experiments, participants learned to classify items into three categories. Across participants, two of the categories were fixed, but the third varied. The results show a violation of IIA in a categorization context. That is, the location of the third category shifted relative preference for the fixed categories. The GCM qualitatively accounts for the data only when category biases are allowed to vary across conditions. A rule-based categorization model with a stochastic criterion did not fit the data as well. In two subsequent experiments, we show that participants did not violate IIA when learned categories were fixed, but category choice sets were varied on a trial-by-trial basis.