منابع مشابه
IGLUE: An Instance-Based Learning System over Lattice Theory
Concept learning is one of the most studied areas in machine learning. A lot of work in this domain deals with decision trees. In this paper, we are concerned with a diierent kind of technique based on Galois lattices or concept lattices. We present a new semi-lattice based system, IGLUE, that uses the entropy function with a top-down approach to select concepts during the lattice construction....
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An instance theory of attention and memory (ITAM) is presented that integrates formal theories of attention and memory phenomena by exploiting commonalities in their formal structure. The core idea in each theory is that performance depends on a choice process that can be modeled as a race between competing alternatives. Attention and categorization are viewed as different perspectives on the s...
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This article presents a theory in which automatization is construed as the acquisition of a domainspecific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur only after practice in a consistent environment. Practice is important because it increases the am...
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Multi-instance (MI) learning is a variant of supervised machine learning, where each learning example contains a bag of instances instead of just a single feature vector. MI learning has applications in areas such as drug activity prediction, fruit disease management and image classification. This thesis investigates the case where each instance has a weight value determining the level of influ...
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ژورنال
عنوان ژورنال: Learning & Behavior
سال: 2011
ISSN: 1543-4494,1543-4508
DOI: 10.3758/s13420-011-0046-2