Schulmeister, B.B.SchulmeisterBleich, M.M.Bleich2022-03-092022-03-091995https://publica.fraunhofer.de/handle/publica/324421This paper describes the hybrid algorithm DIPOL-DT which uses the strengths of standard decision tree algorithms and piecewise linear classifiers because at every level of learning it chooses the appropriate subdivision of the attribute space: a split with hyperplanes in general position or an axis-parallel split. The proposed method combines two existing algorithms - the piecewise linear classification algorithm DIPOL and the decision tree algorithm CAL5. To some extent the strength of each individual method complements the weaknesses of the other.enclassificationdecision treeEntscheidungsbaumKlassifikationmachine learningmaschinelles Lernen400004005006conference paper