Decision tree model

About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.

Research on ID3 Decision Tree Classification Algorithm Based on MapReduce

Abstract: Decision tree is widely used in data mining which is one of the typical classification algorithms.Traditional ID3 tree learning algorithms require training data to reside in memory on a single machine,so they cannot deal with massive datasets.To solve this problem,this paper analyzes the parallel algorithm of ID3 decision tree based on MapReduce model,then proposes a parallel and distributed algorithm for ID3 decision tree learning.The experimental results demonstrate the algorithm can scale well and efficiently process large-scale datasets on commodity computers.

Real Computation and Complexity

Abstract: On the Complexity of Real Equation Solving by Bernd Bank, Humboldt–Universität zu Berlin The first part of the speech deals with the particular case of integer points in a semi-algebraic set described by quasi-convex polynomial inequalities in the n–dimensional real space. The simply exponential bounds are “optimal” with respect to the dense codification of the polynomials. Without changing the data structure there is no hope to improve the complexity. In a second part it is discussed, what can be expected if the method recently developed by GIUSTI/ HEINTZ/ MORAIS/ MORGENSTERN/ PARDO is transferred to the real case. This method finds the isolated points in a zero–dimensional affine variety. Its main features are the use of straight line programs as data structure and the polynomial sequential time measured in both, the length of the input description and an appropriate affine “geometric” degree of the equation system. The main result with respect to the real case is the following: the transferred method finds a representative point with algebraic coordinates of each connected component of a given smooth and compact real hypersurface. A suitably defined “real degree” of some polar variety corresponding to the input equation describing the hypersurface in question replaces the affine geometric degree of the equation system. On Bounding the Betti Numbers of Semi-Algebraic Sets by Saugata Basu, Courant Institute, New York University In this talk we give a new bound on the sum of the Betti numbers of semialgebraic sets. This extends a well-known bound due to Oleinik and Petrovsky, Thom and Milnor. In separate papers they proved that the sum of the Betti numbers of a semi-algebraic set S ⊂ R, defined by P1 ≥ 0, . . . , Ps ≥ 0, deg(Pi) ≤ d, 1 ≤ i ≤ s, is bounded by (O(sd)). Given a semi-algebraic set S ⊂ R defined

Maya-Based Simulation of Tree Movement with Electronic Image Processing

Abstract: According to the motion characteristics of the trees in the wind, the paper builds a realistic virtual simulation of three-dimensional plant movement on Maya with electronic image processing The main purpose is to provide realistic effect for many applications fields, such as games, movies and so on Firstly, the tree model is established on basis of polygon modeling tools with electronic image processing Secondly, the force is analyzed and bone is created so as to set reasonable bone controller to drive the movement of the tree model Finally, we realized the swing and fracture based on the principle of dynamic and cloth solver is adopted to make the swing and falling of the tree leafs more natural The whole process mainly includes the gravity field; the wind field and the key frame technology Experiments show that the method not only reduces the development time and work, but also makes the movement of trees more realistic

Decision Tree Algorithm Based on Association Rules

Abstract: This paper combines association rules and decision tree algorithm,and proposes a new decision tree classification based on association rule.The decision tree algorithm can handle dissimilar transaction data set record blocks which are same investigations conducted in different times to the same transactions.Through the decision tree algorithm,it can get a multi-crunodes decision tree,which has a good extendable performance.The algorithm solves the problem,which exists in the traditional classification,that is the traditional classification can not classify effectively and sustaine when dimensions of dataset change.