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Določanje mejne odločitvene poti z uporabo metode podpornih vektorjev
Rebernak, Damijan ; Zorman, Milan ; Lenič, Mitja
Knowledge representation is one of major drawbacks of most machine learning approaches. Decision trees machine learning method is well known .for straighforward knowledge representation. Despite ...rule-based knowledge representation we noticed some problems during data extraction in cases when several different rules for same decision exist. Our idea was to outline more important rules and to notify user about more critical paths in the decision tree. Support vector machines are learning machines designed to automatically deal with the accuracy/generalisation trade-off, by minimizing an upper bound on the generalisation error provided by VC theory. That makes them very attractive for applications in different domains especially in the field of medical diagnoses. Combining these two approaches we got a hybrid decision tree, capable of giving us additional information about critical paths and rules.
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