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

Katholieke Universiteit Leuven, Dept. of Computer Science, Celestijnenlaan 200A, B-3001 Leuven, Belgium ... Cross-validation is a useful and generally ap- ... t∗ := optimal test(T). P := partition induced on T by t∗ if stop criterion(P) then retu

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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

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

May 23, 2016 - that the hyperplane partitioning can be replaced with ball partitioning, which can further improve the search performance. ... Keywords: GNAT, EGNAT, AESA, metric space indexing, generalized hyperplane partitioning, ball partitioning.

Aug 23, 2016 - A geometric constraint problem, also known as a geometric constraint system, consists of a finite set of ... 3. the understanding of spatial constraint systems, see Section 5. We also look briefly at ..... Concerning the second questio

Aug 23, 2016 - Restricted to points and distances, the constraint graph analysis has deep roots ... fies all equations. Viewed in this foundational way, solving a GCS boils down to formulating a system of equations in the coordinates of the geometric

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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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

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

Nov 4, 2016 - analysis shows that this algorithm can learn a near optimal decision tree, since it can find the best ... In recent years, with the emergence of very big training data (which cannot be held in one single ... (1993)], which require the t

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Mar 24, 2014 - tations for new developments, both in well-established and contemporary scientific tasks. However, this ... the qualitative performance of methods, imperilling their accuracy as well as their robustness in the case of noise .... [3] st

Aug 31, 2007 - Survey), DENIS (the Deep Near Infrared Survey), DIVA , GAIA, etc., astro- nomical data are measured by Terabyes, .... A book describing the software was published in 2005 by Ian H. ... methods include instance-based learning algorithms