Measuring similarity judgments with machine-learning algorithms

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Contributors:
  3. Tanner Rasumussen

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Description: This project uses machine-learning algorithms to predict similarity judgments to (1) investigate which algorithms best predict similarity judgments, (2) assess which predictors are most useful in predicting similarity judgments, and (3) determine the minimum number of questions required to accurately predict similarity judgments.

License: CC-By Attribution 4.0 International

Has supplemental materials for Improving measurements of similarity judgments with machine-learning algorithms on PsyArXiv

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Stevens, J.R., Polzkill Saltzman, A., Rasmussen, T., & Soh, L.-K. (2020). Improving measurements of similarity judgments with machine-learning algorithms. Abstract: Intertemporal choices involve assessing options with different reward amounts available at different time delays. The similarity approach to intertemporal choice focuses on judging how similar amounts and delays are, yet we do not full...

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