First order random forests: Learning relational classifiers with complex aggregates

Abstract

In relational learning, predictions for an individual are based not only on its own properties but also on the properties of a set of related individuals. Relational classifiers differ with respect to how they handle these sets: some use properties of the set as a whole (using aggregation), some refer to properties of specific individuals of the set… (More)
DOI: 10.1007/s10994-006-8713-9

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