Models of incremental concept formation
Artificial Intelligence
Concept learning and heuristic classification in weak-theory domains
Artificial Intelligence
Conceptual Clustering, Categorization, and Polymorphy
Machine Learning
Machine Learning
Experiments with Incremental Concept Formation: UNIMEM
Machine Learning
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Concept Learning with Incomplete Data Sets (Master''s Thesis)
Concept Learning with Incomplete Data Sets (Master''s Thesis)
Concept formation by incremental conceptual clustering
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Concept formation vs. logistic regression: predicting death in trauma patients
Artificial Intelligence in Medicine
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This research effort represents an inquiry into an important problem of automated acquisition, indexing, retrieval, and effective use of knowledge in diagnostic tasks. Its specific goal is to develop an incremental concept formation system which will automate both the design and use of diagnostic knowledge-based systems by a novice. The adopted approach to this problem is based on the modified family resemblance and contrast model theories, as well as a context-sensitive, distributed probabilistic representation of learned concepts. These ideas have been implemented in the INC2 system. The system is evaluated in terms of its prediction accuracy in the domains of breast cancer, primary tumor, and audiology cases.