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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.
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TL;DR: This paper extends some of the results related to the comparison of one-variable complexity functions using complexity classes to multivariable complexity functions.
Abstract: The comparison of algorithms complexities can be r educed to the comparison of complexity functions. In two previous papers, we obtained some results related to the comparison of one-variable complexity functions usi ng complexity classes. In this paper, we extend some of these results to multivariable co mplexity functions.
01 Jul 2014
TL;DR: The experimental results suggested that the interactive visual decision tree (IVDT) process can improve the effectiveness of modeling in terms of producing trees with relatively high classification accuracies and small sizes, enhance users’ understanding of the algorithm, and give them greater satisfaction with the task.
Abstract: In the social sciences, meta-analysis has been used on a limited scale only, mainly because there still remains a gap between the knowledge available and itsapplication in policymaking. The experimental results suggested that, compared to the automatic modeling process as typically applied in current decision tree modeling tools, interactive visual decision tree (IVDT) process can improve the effectiveness of modeling in terms of producing trees with relatively high classification accuracies and small sizes, enhance users’ understanding of the algorithm, and give them greater satisfaction with the task.
01 Jan 2013
TL;DR: A way to change the structure of the decision tree to improve the quality of classification is proposed and the split criterion is based on the confusion matrix.
Abstract: This paper presents the problem of sequential decision making in the pattern recognition task. This task can be presented using a decision tree. In this case, it is assumed that the structure of the decision tree is determined by experts. The classification process is made in each node of the tree. This paper proposes a way to change the structure of the decision tree to improve the quality of classification. The split criterion is based on the confusion matrix. The obtained results were verified on the basis of the example of the computer-aided medical diagnosis.
Patent•
02 Apr 2014
TL;DR: In this paper, a method for reconstructing a tree model based on a point cloud and data driving is presented, which comprises the following steps that tree point cloud data are acquired and preprocessed, and classification representation of the tree model is defined; a cylinder moving method is provided and used for extracting main branch framework points from the tree point clouds data, and branch and leaf separation processing is carried out; crown feature points are extracted from the Tree Point Cloud data; a classification ion flow method was used for structuralizing the main branches framework points and the crown features points; the
Abstract: The invention discloses a method for rebuilding a tree model based on a point cloud and data driving. The method comprises the following steps that tree point cloud data are acquired and preprocessed, and classification representation of the tree model is defined; a cylinder moving method is provided and used for extracting main branch framework points from the tree point cloud data, and branch and leaf separation processing is carried out; crown feature points are extracted from the tree point cloud data; a classification ion flow method is provided and used for structuralizing the main branch framework points and the crown feature points; the complete tree model is obtained in a rebuilding mode according to the structuralized framework points and radiuses of all the branches. A solution scheme is provided for rebuilding the complete tree model in the three-dimensional point cloud data, the obtained rebuilt model and an original point cloud have the high fit degree, and the good rebuilding result can be obtained on models which are severely blocked and are complex in form.