منابع مشابه
Complexity Measures and Concept Learning
The nature of concept learning is a core question in cognitive science. Theories must account for the relative difficulty of acquiring different concepts by supervised learners. For a canonical set of six category types, two distinct orderings of classification difficulty have been found. One ordering, which we call paradigm-specific, occurs when adult human learners classify objects with easil...
متن کاملComplexity Measures and Classification Learning
In classification learning experiments, test subjects are presented with objects which they must categorize. The correct categories, which are known to the experimenter, are functions of the characteristics (“dimensions”) of the objects, such as size, color, brightness, and saturation. The experiments measure the relative difficulty of learning different categorizations. One major factor which ...
متن کاملConcept learning using complexity regularization
We apply the method of complexity regularization to learn concepts from large concept classes. The method is shown to automatically find a good balance between the approximation error and the estimation error. In particular, the error probability of the obtained classifier is shown to decrease as O(dm) to the achievable optimum, for large nonparametric classes of distributions, as the sample si...
متن کاملSimplicity and complexity in human concept learning
The topic I’d like to talk to you about today is, I think, one of the oldest and most basic in cognition: how we learn from examples. As most famously pointed out by Hume, when we make a finite number of observations of an enduring phenomenon, there is no strictly logical (i.e., deductive) basis for forming any firm generalizations about it. Instead we must “induce,” that is, make educated gues...
متن کاملCategorical invariance and structural complexity in human concept learning
An alternative account of human concept learning based on an invariance measure of the categorical stimulus is proposed. The categorical invariance model (CIM) characterizes the degree of structural complexity of a Boolean category as a function of its inherent degree of invariance and its cardinality or size. To do this we introduce a mathematical framework based on the notion of a Boolean dif...
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ژورنال
عنوان ژورنال: Journal of Mathematical Psychology
سال: 2015
ISSN: 0022-2496
DOI: 10.1016/j.jmp.2015.01.001