Localized Exploratory Projection Pursuit
نویسنده
چکیده
Based on CART, we introduce a recursive partitioning method for high dimensional space which partitions the data using low dimensional features. The low dimensional features are extracted via an exploratory projection pursuit (EPP) method, localized to each node in the tree. In addition, we present an exploratory splitting rule that is potentially less biased to the training data. This leads to a nonparametric classiier for high dimensional space that has local feature extractors optimized to diierent regions in the input space.
منابع مشابه
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