Efficient splitting rules based on the probabilities of pre-assigned intervals
June-Suh Cho, Nabil R. Adam · 2002
The paper describes novel methods for classification in order to find an optimal tree. Unlike the current splitting rules that are provided by searching all threshold values, the paper proposes splitting rules that are based on the probabilities of pre-assigned intervals. In experiments, we demonstrate that our methods properly classify image objects based on new split rules.