论文信息 - Local Application of One-Level Trees

Local Application of One-Level Trees

We propose a technique of local application of one-level decision and regression trees. We recognize local regions having similar characteristics and then build local expert on each of these regions describing the relationship between the data characteristics and the target value. We performed a comparison with other well known lazy methods on standard benchmark datasets and the proposed technique produced the most accurate results.

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