Abstract
Statements of the major tasks of inductive formation of knowledge are suggested. These are classifications and clusterings, which are part of machine learning and are applied for dependence models with parameters that are not flawed in their traditional statement. An algorithm for knowledge base formation is presented for learning samples in almost real-life ontologies of medical diagnosis.
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Original Russian Text © A.S. Kleschev, S.V. Smagin, 2012, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2, 2012, No. 1, pp. 9–21.
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Kleschev, A.S., Smagin, S.V. Problems of inductive formation of knowledge in the ontology of medical diagnosis. Autom. Doc. Math. Linguist. 46, 8–21 (2012). https://doi.org/10.3103/S0005105512010037
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DOI: https://doi.org/10.3103/S0005105512010037
Keywords
- machine learning
- inductive formation of knowledge
- task of classification
- a dependence model with parameters
- an easily interpreted dependence model
- a learning algorithm
- an experimental study of properties
- model data
- evaluation of internal properties
- evaluation of external properties
- ontologies of medical diagnosis