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Regularizing soft decision trees
(Springer, 2013)
Recently, we have proposed a new decision tree family called soft decision trees where a node chooses both its left and right children with different probabilities as given by a gating function, different from a hard ...
Univariate margin tree
(Springer, 2010)
In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we propose a new decision tree learning algorithm called univariate margin ...
Statistical tests using hinge/ε-sensitive loss
(Springer-Verlag, 2013)
Statistical tests used in the literature to compare algorithms use the misclassification error which is based on the 0/1 loss and square loss for regression. Kernel-based, support vector machine classifiers (regressors) ...