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检索条件"主题词=ID3 Algorithm"

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A DECISION MODEL OF idENTIFYING USER TRAVEL PATTERN BASED ON THE INTELLIGENT TERMINAL SENSOR DATA 4

A DECISION MODEL OF IDENTIFYING USER TRAVEL PATTERN BASED ON...

引用

4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS)

作者： Wang, Shuai Xiu, Jiapeng Liu, Chen Yang, Zhengqiu Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China

ISBN: (纸本)9781509012565

The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern decision model based on the sensor data. The decision algorithm adopts decision tree algorithm based on id3. Experiments data shows that this decision model is effective in identifying the pattern of user's travel.

关键词： User travel Pattern Sensor Data Travel pattern identifying Decision tree id3 algorithm

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Retail Commodity Sale Forecast Model Based on Data Mining 8

Retail Commodity Sale Forecast Model Based on Data Mining

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8th International Conference on Intelligent Networking and Collaborative Systems (INCoS)

作者： Zhang, Jing Li, Juan Officers Coll CAPF Basic Comp Teaching & Res Sect Chengdu Sichuan Provinc Peoples R China

ISBN: (纸本)9781509041237

In terms of the retail commodity sale forecast, people did more in particular aspect with commodity's single sale attribute such as the sale volume, the sale money, the season factor, but all has not considered the most important factor profit, the profit is the key factor of retail enterprises winning the survival and development. However, such a one-sided analysis is not conducive to assist the managers understand the overall situation of retail sales, and make the decision the sale and the inventory. So this paper firstly selected the profit ratio which was on behalf of commodity profit element and several other key sale attributes including the season ratio and the sale volume to establish the SPV Model;secondly done commodity sale state segmentation based on the SPV Model with id3 decision tree algorithm, And on this basis we predicted the sale state of the commodity at some future time;Finally, we compared and analysis the results of the SPV Model, the Season Model and the Markov Model through experiments, and get the conclusion that the SPV Model can reach higher correctness than the other two.

关键词： SPV Model the profit ratio grade the season ratio the sale volume id3 algorithm

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The data mining method based on second learning

The data mining method based on second learning

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7th International Conference on Machine Learning and Cybernetics

作者： Li, Yan Li, Guo-Gang Li, Fa-Chao Jin, Chen-Xia Hebei Univ Sci & Technol Sch Sci Shijiazhuang 050018 Peoples R China Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050018 Peoples R China

ISBN: (纸本)9781424420957

Decision tree algorithm is not only the important part of machine learning, but also the most widely used data mining tool. At present, there are many algorithms of generating decision tree, but when the database which we rely on exists noise, high quality knowledge is hard to obtain by id3 algorithm. In this paper, we propose the data mining method based on second learning in case of id3 algorithm, and analyze the performance of our method by a concrete database. Theory analysis and simulation indicate that this method posses the feature of strong operability, and it can improve the reliability of obtained knowledge.

关键词： decision tree id3 algorithm noise second learning accuracy rate

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A Flash Light System for Individuals with Visual Impairment Based on TPVM 7

A Flash Light System for Individuals with Visual Impairment ...

引用

7th International Conference on Cloud Computing and Big Data (CCBD)

作者： Fang, Wenbin Zhai, Guangtao Yang, Xiaokang Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Shanghai Peoples R China

ISBN: (纸本)9781509035557

We propose a flashlight system to aid visually impaired people using the paradigm of temporal psychovisual modulation (TPVM), which is new display mode taking advantage of the limited flicker fusion frequency of human eyes and high refresh rate of modern display devices to achieve visual bifurcation effect. Structured light in visible spectrum is projected out onto the road surface and a synchronized camera detects the deformation and then the recognition system calculates the road flatness (e.g. smooth road, up-or downstairs). To minimize the visual disturbance to other people, the TPVM display technique effectively conceals the structured light and making it basically a normal flashlight to normal observers. The system works in visible spectrum to minimize cost of the camera and the projector. We design fast and reliable recognition system with iterative dichotomiser 3(id3) algorithm to differentiate condition of the pavement ahead into smooth road, wall ahead and up/down-stairs. Experimental results are presented to validate the proposed system.

关键词： flash light visual impairment temporal psychovisual modulation image patterns id3 algorithm

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Application of decision tree in XML database mining 8

Application of decision tree in XML database mining

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8th International Conference on Intelligent Computation Technology and Automation (ICICTA)

作者： Liao Shaowen Qiu Decheng Chen Yong Hexi Univ Informat Technol & Media Inst Zhangye 734000 Gansu Peoples R China Artillery Training Base Gen Staff XuanHua Zhangjiakou 075100 Hebei Peoples R China

ISBN: (纸本)9781467376440

Traditional data mining is based on relational database, XML (extensible markup language) technology has become as a standard for representing and exchanging information in a short period of time, a new data mining method is provided, and this paper gives a brief introduction to decision tree and XML technology, as well as XML-based data mining basic process of the study. Then a novel model of the decision tree analysis based on the XML database is presented. Finally, through an example how to use this model for data mining is illustrated, and the direction of future research in the decision tree is pointed out.

关键词： Decision tree id3 algorithm information theory XML database data mining

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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 Research and Analysis in Decision Tree algorithm Based on C4.5 algorithm 3

The Research and Analysis in Decision Tree Algorithm Based o...

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3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Hao, Huan Chen, Tieming Lu, Jing Liu, Jie Ma, Xiaodan Xian High Tech Inst Tongxin Rd 2 Xian Shaanxi Peoples R China

ISBN: (纸本)9781538645093

On the base of introducing the Decision Tree, this article lists two main algorithms of Decision Tree. After describing the principle of briefly, it reveals the essential idea and the computing process of C4.5 algorithm in detail. As constructing a Decision Tree on a group of instance data with the two algorithms, we get the principle of classification about the data. By comparing the two algorithms during the process of constructing the tree, we analysis the advantages and disadvantages of them finally. With the conclusion of the applied scope of each algorithm, it provides a theoretical basis for choosing an appropriate method in practical application.

关键词： The Decision Tree C4.5 algorithm id3 algorithm

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Performance Improvement Validation of Decision Tree algorithms with Non-normalized Information Distance in Experiments 19th

Performance Improvement Validation of Decision Tree Algorith...

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19th Pacific Rim International Conference on Artificial Intelligence (PRICAI)

作者： Araki, Takeru Luo, Yuan Guo, Minyi Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9783031208614;9783031208621

The performance of id3 algorithm in decision tree depends on the information gain but it has a drawback because of tending to select attributes with many values as the branching attributes. The gain ratio (especially in C4.5) is proposed to improve the information gain, but it does not always improve the performance, nor is it always defined. Some scientists use normalized information distance to improve the gain ratio, however, it is ineffective. In this paper, we investigate two non-normalized information distance selection criteria to replace the information gain and the gain ratio and conduct detailed experiments on 13 datasets classified into four types with theoretical analysis. Surprisingly, on the datasets where the number of values of each attribute differ greatly i.e. in Type1 and Type2, non-normalized information distance-based algorithms can increase the accuracy of about 15-25% of id3 algorithm. The first reason is that more values for an attribute does not reduce the distances, which is suggested by Mantaras. The second reason is that the conditional entropy which is the opposite one used in the information gain can bring balance to the multi-valued biased values. Furthermore, our methods can maintain results comparable to those of existing algorithms on other cases. Compared to the gain ratio, the algorithms with non-normalized information distances conquer the drawback much better on Type1 datasets, which is strongly confirmed by experiments and corresponding analysis. It can be presumed that "normalization" improvement methods such as normalized information distance and the gain ratio are not always effective.

关键词： Decision tree id3 algorithm Information distance Information gain Gain ratio

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Improving change proneness prediction in UML based design models using ABC algorithm 3

Improving change proneness prediction in UML based design mo...

引用

3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Godara, Deepa Singh, R. K. Uttarakhand Tech Univ CSE Chandanwadi India

ISBN: (纸本)9781479930807

In the field of software engineering, which is emerging as the undisputed man of the match in the ever-changing sports of sophistications, the incessant changes effected in software every day have assumed such an alarming proportion causing untold and unimagined paradoxes that it is highly essential to initiate instant and immediate steps to balance this blitz. It does not mean that no endeavor has been made in the bye-gone era to tackle the issue. In fact, several methods to solve this dilemma were introduced in the past by predicting the changes in the software. But these methods have miserably met with a waterloo in facilitating a highly appreciable forecast harvest. To handle this problem with an eye on good prediction accuracy, a new method is introduced in our paper. The two phases in our proposed work are: (1) Feature identification (2) Classification of classes for the change-proneness prediction. In feature identification phase, the features obtained from any input application are time, trace events, behavioral dependency, frequency and popularity, which help to predict the change proneness in our work. There are three ways by which these five features are found from the application. They are: Features obtained directly from an application such as time, trace events;Features obtained from UML Diagrams such as behavioral dependency and Features obtained from optimal frequent item set mining and ABC such as frequency and popularity. Thus all these five features are obtained from our proposed work and then in the classification phase, these features are given as the input to the id3 decision tree algorithm for effectively classifying the classes according as whether it predicts the change proneness or not. If a class is classified into prediction of change prone class, then the value of change proneness is also obtained by our work.

关键词： Change-prone Artificial Bee Colony algorithm Frequent item set mining Association rule mining id3 algorithm decision tree

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Analysis on the fuzzy filter in fuzzy decision trees

Analysis on the fuzzy filter in fuzzy decision trees

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International Conference on Machine Learning and Cybernetics

作者： Li, FC Sun, J Wang, XZ Hebei Univ Sci & Technol Coll Sci Shijiazhuang 050018 Peoples R China

ISBN: (纸本)0780378652

Fuzzy decision tree, which is an extension of classical decision tree, is an effective method to extract knowledge in uncertain classification problems. The essential characteristic of fuzzy decision tree is to take of the value in [0, 1] to describe the subordinate relation between examples and linguistic terms, This avoids the unreasonability generated by the classical decision tree, which only use 0 and 1 to describe the subordinate relation. By well using the relation between examples and attributes, the fuzzy decision tree holds high performance, but at the same time, this fuzziness leads to the uncertainty of classification and disturb the building of a good decision tree. So, how to filter fuzzy data properly is an important segment in the building and the application of decision trees. This paper analyzes the effect of fuzzy filter on the fuzzy decision tree by using many experiments, which are based on both fuzzy id3 heuristic method and the minimal ambiguity based heuristic method. This paper also discusses the fuzzy filter level from both the inherent mechanism of building a fuzzy decision tree and the essence of fuzzy information filter, and proposes a practical method to determine this filter level for different data sets.

关键词： fuzzy decision tree fuzzy filter level id3 algorithm learning from example

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