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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 study presents a low-cost method for estimating SBSTs in large rural areas based on building features extracted from remote sensing data and building-related local knowledge expressed as building group pattern-SBST correlations using the decision tree model and statistical methods.
Abstract: The seismic building structural type (SBST) represents critical information for accurately assessing seismic risk. Such risk is typically determined as a function of seismic hazards, assets such as buildings and people exposed to hazards, and the vulnerability of those exposed elements (especially buildings because SBSTs dictate the main load-bearing structures of buildings and their seismic vulnerability). China has vast rural areas that generally differ in building upgrade status. SBST distribution information for these areas is often outdated, missing, or nonexistent, thus hindering local governments’ planning for earthquake preparedness and mitigation. This study presents a low-cost method for estimating SBSTs in large rural areas. According to building features (e.g., footprint, roof type) extracted from remote sensing data and building-related local knowledge (BRLK) expressed as building group pattern-SBST correlations, a series of SBST recognition rules is established using the decision tree model and statistical methods. The results from experimental verification show the following. Using only decision tree-based recognition, the estimation of SBSTs reaches an overall accuracy of approximately 70%. After combining decision tree-based recognition with BRLK, the overall estimation accuracy exceeds 90%. The proposed method establishes reliable recognition rules for estimating SBSTs in large rural areas and has a strong potential for popularization and application. In the future, the proposed method can be further investigated according to the BRLK in various areas in terms of applicability and adjustment schemes.

4 citations

Journal ArticleDOI
TL;DR: Through the No Free Lunch Theorem (NFL) revelation, the original PSO algorithm is improved to enhance the validity of the original decision tree.
Abstract: For the relationship of environmental parameters and variables in the each transport process, by using data mining, the system gets the corresponding decision tree. In a certain environment parameters conditions, the occurrence of the event is determined by the decision tree. Through the No Free Lunch Theorem (NFL) revelation, the original PSO algorithm is improved to enhance the validity of the original decision tree. To the final experiments results, once again demonstrate the improved algorithm is efficient.

4 citations

01 Jan 2012
TL;DR: A comparative study on ID3, FID3 and PFID3 is done, using fuzzy set theory to describe the connected degree of attribute values, which can precisely distinguish the deference of subordinate relations between different examples and every attribute values.
Abstract: Decision tree (DT) is a very practical and popular approach in the machine learning domain for solving classification problems in data mining . Decision tree learning algorithm has been successfully used in expert systems in capturing knowledge. The main task performed in these systems is using inductive methods to the given values of attributes of an unknown object to determine appropriate classification according to decision tree rules. In the past, ID3 was the most used algorithm in this area . This algorithm is introduced by Quinlan, using information theory to determine the most informative attribute. A disadvantage of decision tree is its instability. Decision tree is recognized as highly unstable classifier. The structure of the decision tree may be entirely different if some things change in the dataset. To overcome this problem, some scholars have suggested Fuzzy Decision Tree (e.g. FuzzyID3) by utilizing the fuzzy set theory to describe the connected degree of attribute values, which can precisely distinguish the deference of subordinate relations between different examples and every attribute values. After some years PFID3 was also introduced which was called as probabilistic fuzzy ID3. In this paper, a comparative study on ID3, FID3 and PFID3 is done.

4 citations

Journal ArticleDOI
TL;DR: The results show that the sphere-board-based tree model (SBTM) can achieve a better compromise between realism and performance than can the BBTM or CPTM and can better support lighted effects because of its cubic geometrical features.
Abstract: Because of the smooth interaction of tree systems, the billboard and crossed-plane techniques of image-based rendering (IBR) have been used for tree visualization for many years. However, both the billboard-based tree model (BBTM) and the crossed-plane tree model (CPTM) have several notable limitations; for example, they give an impression of slicing when viewed from the top side, and they produce an unimpressive stereoscopic effect and insufficient lighted effects. In this study, a sphere-board-based tree model (SBTM) is proposed to eliminate these defects and to improve the final visual effects. Compared with the BBTM or CPTM, the proposed SBTM uses one or more sphere-like 3D geometric surfaces covered with a virtual texture, which can present more details about the foliage than can 2D planes, to represent the 3D outline of a tree crown. However, the profile edge presented by a continuous surface is overly smooth and regular, and when used to delineate the outline of a tree crown, it makes the tree appear very unrealistic. To overcome this shortcoming and achieve a more natural final visual effect of the tree model, an additional process is applied to the edge of the surface profile. In addition, the SBTM can better support lighted effects because of its cubic geometrical features. Interactive visualization effects for a single tree and a grove are presented in a case study of Sabina chinensis. The results show that the SBTM can achieve a better compromise between realism and performance than can the BBTM or CPTM.

4 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202310
202224
2021101
2020163
2019158
2018121