Geometric Decision Tree

Nov 16, 2016 - decision tree is because of its simplicity and easy interpretability as a classification rule. In a decision tree classifier, each non-...

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Feb 24, 2018 - Incremental Learning, Decision Trees, Classification. ACM Reference Format: Chaitanya Manapragada, Geoffrey I. Webb, and Mahsa Salehi. 2018. Ex- tremely Fast Decision Tree. In Proceedings of ACM conference (KDD'18). ACM,. New York, NY,

Apr 14, 2015 - that it can handle both qualitative and quantitative features in the same oblique split. Keywords: Oblique decision tree, Data classification, Statistical learning, Householder reflection, Machine learning. 1. ..... 2 HHCART(A) - Compl

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May 10, 2007 - be used to discover production rules in warehouses or corporate data. Data ... practice, the long processing time required by data mining algorithms remains a ... very definition. Indeed, we can make an analogy between building success

quence yields the highest cumulative probability. By combining a stack decoder search with a breadth- ... the relative likelihood that each choice is the one which should be selected. 2.1 What is a Decision Tree? .... cal estimates, i.e. relative-fre

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Feb 18, 2013 - The decision tree model captures the complexity of computing functions f : Xm → Y in a setting where the quantity of interest is the number of queries to the input (see [1] for a good review of the model). We are allowed to query ind

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Aug 22, 2000 - which the oracle and the computer exchange several rounds of messages, each round consisting of O(log ... Unlike classical decision trees, a quantum decision tree algorithm can make queries in a quantum ... and by degree of approximati

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For example, the number of paths arriving at clauses c7, c8, c9, and c10 in Figure 4 are. 3C0, 3C1, 3C2, and 3C3, respectively. Hence, this decision tree is termed as a binomial decision tree constructed with indistinguishable variable pairs. In this

Apr 6, 2015 - The goal is to compute f(x), while minimizing the number of queries made to the black box. For a function f : {0,1}n → {0,1}, let D(f) denote the deterministic query complexity (or decision tree complexity) of computing f, the minimum

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