Machine learning-based measure of cognitive complexity explains variance in rank-ordered preference.
Shabnam HakimiYan-Ying ChenMonica P. VanScott A. CarterEmily SumnerNayeli Suseth BravoKalani MurakamiYanxia ZhangCharlene C. WuMatthew KlenkPublished in: CogSci (2023)
Keyphrases
- machine learning
- complexity measures
- machine learning methods
- decision trees
- knowledge discovery
- correlation coefficient
- computational complexity
- learning algorithm
- similarity measure
- artificial intelligence
- user preferences
- information processing
- learning tasks
- natural language
- pattern recognition
- data mining
- machine learning approaches
- space complexity
- prediction error
- standard deviation
- relative entropy
- inductive logic programming
- explanation based learning
- kl divergence
- text classification
- distance measure
- information extraction
- model selection
- knowledge acquisition
- multi attribute
- worst case
- supervised learning
- cognitive processes
- reinforcement learning
- soft constraints
- decision making
- feature selection
- computer vision