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HEURISTIC MODE RESEARCH OF DECISION TREE algorithm BASED ON SYNTHESIZING EFFECT

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2011年第9期7卷 5327-5339页

作者： Li, Fachao Guan, Fei Shi, Yan Hebei Univ Sci & Technol Sch Sci Shijiazhuang 050018 Peoples R China Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050018 Peoples R China Tokai Univ Sch Ind Engn Kumamoto 8628652 Japan

Decision tree, as a simple classification algorithm, is an effective tool for mining knowledge rules, and it has been successfully applied in many fields. Based on the analysis of the essential characteristics of decision tree algorithm for the selection of the expanded attributes, we put forward leaf criterion which can recognize the extension ability of attributes, data utilization criterion and comprehensive effect criterion. Further, we establish a mathematical model with structural characteristics which can evaluate the extension capabilities of attributes, and also give a selection model of expanded attributes based on quasi-linear function (denoted by QASM, for short). Finally, we compare and analyze the performance of QASM combining with id3 algorithm through different examples. All the results indicate that QASM can effectively merge the decision consciousness into decision process in a quantitative way, and that the computational complexity is lower than that of id3 algorithm. Thus, it has wide application and operability.

关键词： Decision tree Rule id3 algorithm Expanded attribute Extension ability Quasi-linear function Comprehensive effect

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Decision trees in selection of featured determined food quality

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ANALYTICA CHIMICA ACTA 2011年第1-2期705卷 261-271页

作者： Debska, B. Guzowska-Swider, B. Rzeszow Univ Technol Dept Comp Chem PL-35041 Rzeszow Poland

The determination of food quality, authenticity and the detection of adulterations are problems of increasing importance in food chemistry. Recently, chemometric classification techniques and pattern recognition analysis methods for wine and other alcoholic beverages have received great attention and have been largely used. Beer is a complex mixture of components: on one hand a volatile fraction, which is responsible for its aroma, and on the other hand, a non-volatile fraction or extract consisting of a great variety of substances with distinct characteristics. The aim of this study was to consider parameters which contribute to beer differentiation according to the quality grade. Chemical (e.g. pH, acidity, dry extract, alcohol content, CO2 content) and sensory features (e.g. bitter taste, color) were determined in 70 beer samples and used as variables in decision tree techniques. This pattern recognition techniques applied to the dataset were able to extract information useful in obtaining a satisfactory classification of beer samples according to their quality grade. Feature selection procedures indicated which features are the most discriminating for classification. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Principal component analysis id3 algorithm Decision tree Classification Feature selection

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Modeling Forest Fires Risk using Spatial Decision Tree

Modeling Forest Fires Risk using Spatial Decision Tree

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3rd Conference on Data Mining and Optimization (DMO)/1st Multi Conference on Artificial Intelligence Technology (MCAIT)

作者： Yaakob, Razali Mustapha, Norwati Nuruddin, Ahmad Ainuddin B. Sitanggang, Imas Sukaesih Univ Putra Malaysia Fac Comp Sci & Informat Technol Serdang 43400 Selangor Malaysia Univ Putra Malaysia Fac Forestry Serdang 43400 Malaysia Bogor Agr Univ Dept Comp Sci Bogor Indonesia

ISBN: (纸本)9781612842127

Forest fires have long been annual events in many parts of Sumatra Indonesia during the dry season. Riau Province is one of the regions in Sumatra where forest fires seriously occur every year mostly because of human factors both on purposes and accidently. Forest fire models have been developed for certain area using the weightage and criterion of variables that involve the subjective and qualitative judging for variables. Determining the weights for each criterion is based on expert knowledge or the previous experienced of the developers that may result too subjective models. In addition, criteria evaluation and weighting method are most applied to evaluate the small problem containing few criteria. This paper presents our initial work in developing a spatial decision tree using the spatial id3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. The algorithm is applied on historic forest fires data for a district in Riau namely Rokan Hilir to develop a model for forest fires risk. The modeling forest fire risk includes variables related to physical as well as social and economic. The result is a spatial decision tree containing 138 leaves with distance to nearest river as the first test attribute.

关键词： forest fires risk spatial decision tree id3 algorithm

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The Decision Tree Application in Agricultural Development

The Decision Tree Application in Agricultural Development

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3rd International Conference on Artificial Intelligence and Computational Intelligence (AICI 2011)

作者： Lu, JingGui Liu, Yi Li, Xiaoli Taiyuan Univ Technol Coll Comp & Software TYUT Taiyuan Peoples R China

ISBN: (纸本)9783642238802

In the agricultural production, There are many factors play a Decisive role in agricultural output through a comprehensive way, to explore the key factors, this paper introduce the id3 algorithms to analyze the various factors affecting trying to identify the core factors of production control. In the article, firstly, introduces the basic concept of decision tree and the id3 algorithm, then analyze Lin Xian's agricultural output value data of 20 years and formed the preliminary decision tree, then combined with actual situation to generate the decision tree clip;Finally, through the experience of agricultural experts, formed the final decision tree to produces more actual set of rules that in agricultural investment decisions, which has the corresponding reference value to improve agricultural output, and has been proved has very good effect.

关键词： Decision tree id3 algorithm Agricultural output

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A Study of Information Collection Technology in Adaptive Learning Systems

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International Conference on Information Technology for Manufacturing Systems (ITMS 2011)

作者： Li Tian Zhou Hong Yuan Yubin Chongqing Univ Technol Coll Comp Sci & Engn Chongqing Peoples R China

ISBN: (纸本)9783037851494

This paper is about the current trend of personalized education, which established a thumbprint information model of Adaptive Learning Systems on the basis of PAPI general model of information. We did some classified analysis and calculation study based on the information collection technologies, mainly about algorithms and improvements in the id3. The useful data and reference are supplied in the system realization for adaptive teaching model.

关键词： Adaptive study id3 algorithm Thumbprint PAPI

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Data Mining based Fragmentation and Prediction of Medical Data

Data Mining based Fragmentation and Prediction of Medical Da...

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2011 3rd International Conference on Computer Research and Development(ICCRD 2011)

作者： Hnin Wint Khaing University of Computer Studies Mandalay Myanmar

ISBN: (纸本)9781612848396

Data mining concerns theories,methodologies,and in particular,computer systems for knowledge extraction or mining from large amounts of *** rule mining is a general purpose rule discovery *** has been widely used for discovering rules in medical *** diagnosis of diseases is a significant and tedious task in *** detection of heart disease from various factors or symptoms is an issue which is not free from false presumptions often accompanied by unpredictable *** the effort to utilize knowledge and experience of numerous specialists and clinical screening data of patients collected in databases to facilitate the diagnosis process is considered a valuable *** this paper,we presented an efficient approach for the prediction of heart attack risk levels from the heart disease ***, the heart disease database is clustered using the K-means clustering algorithm,which will extract the data relevant to heart attack from the *** approach allows mastering the number of fragments through its k parameter. Subsequently the frequent patterns are mined from the extracted data,relevant to heart disease,using the MAFIA （Maximal Frequent Itemset algorithm）*** machine learning algorithm is trained with the selected significant patterns for the effective prediction of heart attack. We have employed the id3 algorithm as the training algorithm to show level of heart attack with the decision *** results showed that the designed prediction system is capable of predicting the heart attack effectively.

关键词： Data mining Heart Disease Frequent Patterns MAFIA（Maximal Frequent Itemset algorithm） id3 algorithm

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A Method for Clustering China's 3G Value-added Service Users

A Method for Clustering China's 3G Value-added Service Users

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2010 2nd International Conference on Multimedia and Computational Intelligence (ICMCI 2010)

作者： Yating Zhang School of Information Central University of Finance and Economics Beijing, China Shuhang Guo School of Information Central University of Finance and Economics Beijing, China Mo Hai School of Information Central University of Finance and Economics Beijing, China

With the arrival of 3G era, mobile value-added services are developing rapidly. To improve the core competitiveness of operators in the telecommunication industry, on the basis of China's telecommunication market, a method based on id3 algorithm and clustering analysis is proposed to screen 3G value-added service users. Firstly, from the perspective of operators and concerning about the features of 3G value- added services, a set of index system for screening 3G value- added service users is established. Secondly, id3 decision model is established, which is used to screen the users. Thirdly, to clearly determine the user clusters, a clustering analysis is used to further divide the screening results. Finally, examples show that our proposed method for screening users based on id3 algorithm and clustering analysis can effectively prospect latent users, and thus help operator make reasonable decisions.

关键词： id3 algorithm Clustering Analysis China’s Telecommunication market 3G Value-added Service Screening users

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Decision Tree algorithm Based on Average Euclidean Distance

Decision Tree Algorithm Based on Average Euclidean Distance

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The 2010 2nd International Conference on Future Computer and Communication(第二届未来计算机与通信国际会议 ICFCC 2010)

作者： Daojing Hu Quan Liu Qicui Yan JiangSu Province Support Software Engineering R&D Center for Information Technology Application in E School of Computer Science and Technology Soochow University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424458219;9781424458240

Traditionally, the algorithm of id3 takes the information gain as a standard of expanding attributes. During the process of selection of expanded attributes, attributes with more values are usually preferred to be selected. To solve such problem, a kind of AED algorithm based on average Euclidean distance in decision tree is proposed in this paper. The algorithm uses the average Euclidean distance as heuristic information. The experiment results show that the improved AED algorithm can avoid the variety bias of id3 algorithm, and has no worse classification precision and less time cost than id3.

关键词： decision tress id3 algorithm variety bias average Euclidean distance

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Approach to Anomaly Traffic Detection in a Local Network

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Journal of Donghua University(English Edition) 2009年第6期26卷 656-661页

作者：王秀英肖立中邵志清 Department of Computer Information Shanghai Xinqiao Vocational and Technical College School of Information Science and Engineering East China University of Science and Technology Department of Computer Science and Information Engineeting Shanghai Institute of Technology

The research intends to solve the problem of the occupation of bandwidth of local network by abnormal traffic which affects normal user's network ***,a new algorithm in this paper named danger-theory-based abnormal traffic detection was *** an advanced id3 algorithm was presented to classify the abnormal *** a new model of anomaly traffic detection was built upon the two algorithms above and the detection results were integrated with *** firewall limits the bandwidth based on different types of abnormal *** show the outstanding performance of the proposed approach in real-time property,high detection rate,and unsupervised learning.

关键词： clanger theory information enlropy id3 algorithm abnormal traffic

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Heuristic Model Research on Decision Tree algorithm

Heuristic Model Research on Decision Tree Algorithm

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International Asia Symposium on Intelligent Interaction and Affective Computing

作者： Li, Fa-Chao Guan, Fei Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang Peoples R China Hebei Univ Sci & Technol Sch Sci Shijiazhuang Peoples R China

ISBN: (纸本)9780769539102

关键词： decision tree id3 algorithm leaf criterion data utilization criterion comprehensive effect extension capability

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