Using the minimum description length principle to infer reduced ordered decision graphs
نویسندگان
چکیده
منابع مشابه
Inferring Reduced Ordered Decision Graphs of Minimum Description Length
We propose an heuristic algorithm that induces decision graphs from training sets using Rissanen's minimum description length principle to control the tradeoo between accuracy in the training set and complexity of the hypothesis description.
متن کاملInferring Reduced Ordered Decision Graphs of Minimal Description Length
The induction of decision trees from labeled training set data [BFOS84, BFOS84, Qui86, QR89] has been a successful approach for the induction of classification rules. However, although decision trees can, in principle, represent any concept, they are not concise representations for some concepts of interest. In particular, the quality of the generalization performed by a decision tree induced f...
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This paper concerns methods for inferring decision trees from examples for classification problems. The reader who is unfamiliar with this problem may wish to consult J. R. Quinlan’s paper (1986), or the excellent monograph by Breiman et al. (1984), although this paper will be self-contained. This work is inspired by Rissanen’s work on the Minimum description length principle (or MDLP for short...
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The minimum description length (MDL) principle states that one should prefer the model that yields the shortest description of the data when the complexity of the model itself is also accounted for. MDL provides a versatile approach to statistical modeling. It is applicable to model selection and regularization. Modern versions of MDL lead to robust methods that are well suited for choosing an ...
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Probabilistic networks can be constructed from a database of cases by selecting a network that has highest quality with respect to this database according to a given measure. A new measure is presented for this purpose based on a minimum description length (MDL) approach. This measure is compared with a commonly used measure based on a Bayesian approach both from a theoretical and an experiment...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 1996
ISSN: 0885-6125,1573-0565
DOI: 10.1007/bf00115299