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检索条件"主题词=c4.5 algorithm"

共 123 条记录，以下是11-20 订阅

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Application of c4.5 algorithm in Evaluation of Railway Large Maintenance Machinery construction

Application of C4.5 Algorithm in Evaluation of Railway Large...

引用

4th International conference on Frontiers of Manufacturing and Design Science (IcFMD 2013)

作者： Zhu, Weiqiao Shi, Tianyun China Acad Railway Sci Inst Comp Technol Beijing 100081 Peoples R China

ISBN: (纸本)9783037859926

With improvement of the level of modernization and mechanization of railway infrastructure maintenance, Railway large maintenance machinery (RLMM) is considered to be one of the main equipment. We have accumulated large amounts of RLMM construction data. How to mine valuable information from these data has become an important research subject. The c4.5 algorithm of decision tree is a useful method of data mining and classification. The paper solves evaluation of RLMM construction problem based on the c4.5 algorithm. By means of extracting the attribute with maximum gain ratio as the root node of the decision tree from training sample data, the evaluation decision tree was constructed. The decision tree modeling of evaluation of RLMM construction was gained by the post-pruning approach. The experimental results and analysis show that this model has high precision and credibility.

关键词： Evaluation Railway Large Maintenance Machinery (RLMM) c4.5 algorithm Decision Tree

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The Application and Research of c4.5 algorithm

The Application and Research of C4.5 Algorithm

引用

International conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Zhao, Hongyan Shandong Yingcai Univ Sch Comp & Informat Engn Jinan Peoples R China

ISBN: (纸本)9783038350125

In the sustainable development of private universities, stable teachers team is the guarantee of talent training. For colleges or universities, it has important significance to analysis the main factors which cause teachers' loss. c4.5 algorithm is a kind of machine learning algorithm in the classification decision tree algorithm. Decision tree is the main technology of data mining classification and prediction. Through the survey data from the information, it establishes the teacher turnover tendency decision tree model using c4.5 algorithm to provide the decision-making basis for the university management work.

关键词： private universities teachers' loss c4.5 algorithm

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A SURVEY ON NEAREST LOcATION DETERMINATION USING c4.5 algorithm

A SURVEY ON NEAREST LOCATION DETERMINATION USING C4.5 ALGORI...

引用

IEEE International conference on Electrical, Instrumentation and communication Engineering (IcEIcE)

作者： Vijayabaskaran, P. S. Nivedha, A. Nivedha, G. Elodie, Dupont Sri Manakula Vinayagar Engn Coll Dept Informat Technol Pondicherry India

ISBN: (纸本)9781509049967

Picking right product from the right place in a cost-effective way is a prime moto behind running online shopping business. Online shopping portal offer a better platform for promoting most of traditional or conventional products. This online platform relies on the principle of nearest location determination of products which provides services in a quick and reliable manner. In this process, there exists mechanism such as j48 and c4.5 algorithm. The objective of this article is to discuss the nearest location determination algorithm and its scopes. Further the article deliver the opportunity and effectiveness of these algorithm in various traditional product or business promotion.

关键词： cost-effective nearest location determination business promotion c4.5 algorithm

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Factors Affecting Household Electrical Usage Using c4.5 algorithm 6

Factors Affecting Household Electrical Usage Using C4.5 Algo...

引用

6th International conference on cyber and IT Service Management (cITSM)

作者： Nasari, Fina Dewi, Rofiqoh Fujiati Univ Potensi Utama Jl KL Yos Sudarso Km 6-5 3 A Medan 20241 Indonesia

ISBN: (纸本)9781538654330

this paper is part of the classification, focusing on the classification of high household electrical usage. Electricity needs are increasing while availability is getting smaller, requiring solution in its utilization to be more effective and efficient. It is important to classify factors that lead to high electricity consumption among households using the c4.5 algorithm. The c4.5 algorithm is a fairly effective algorithm to help shape decision trees. This research is able to classify the high usage of household electricity. The result of this research get the main factor of high household electric usage is the number of family member with the value of gain 84,2%. Testing of rules generated with average test result 81.69%. It is hoped that the future will become the basis for the wider use of electricity.

关键词： electricity c4.5 algorithm clasification Decision tree

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Design and Implementation of Targeting Advertising System based on c4.5 algorithm 4

Design and Implementation of Targeting Advertising System ba...

引用

4th International conference on computer Science and Network Technology (IccSNT)

作者： Wang, Xuefei Shi, Yan Open Univ Harbin Harbin Peoples R China Harbin Vocat & Tech Coll Harbin Peoples R China

ISBN: (纸本)9781467381734

With the development of Big data, cloud storage and data mining, targeting advertising technology has aroused wide attention. So many companies have invested in the target mobile advertising market in this area. Targeting advertising can effectively save resources, reduce capital investment. Aiming at this problem, this paper proposed a new method for targeting advertising based on c4.5 algorithm and cloud storage. The mess data about users, such as user information, user browsing behavior and so on, is stored in the cloud. With c4.5 algorithm, we do mess data processing for data classification. Then, with the results of classification, the server-push blocks push targeted advertising for users. This paper introduces the structure of the system and the detailed analysis of the classification algorithm. And the classification results obtained in this paper are compared with those by other algorithms. It is believed that this paper will be helpful in the development of targeting advertising.

关键词： target advertising Big data c4.5 algorithm

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Based on Tree Structure and c4.5 algorithm Procotol in Wireless Sensor Networks

Based on Tree Structure and C4.5 Algorithm Procotol in Wirel...

引用

8th International conference on Wireless communications, Networking and Mobile computing (WicOM)

作者： Fu, Rong Yu, Min Zou, chengwu Jiangxi Normal Univ Sch Software Nanchang Peoples R China Jiangxi Normal Univ Coll Comp Informat Engn Nanchang Peoples R China

ISBN: (纸本)9781612846835;9781612846828

Wireless Sensor Network (WSN) has been intensely studied because of their potential applications and technological challenges. However, WSN is a large number of resource constrained sensor nodes, which have limited battery and low power operation. consequently, network lifetime becomes an important parameter for efficient design of data gathering schemes for sensor networks. In this paper, to achieve fault tolerance and to extend network lifetime, both cluster and tree structures for data gathering are taken. The novelty of this paper is in its development of a combination use of tree and cluster structured model in WSN while using c4.5 algorithm to choose the suitable parent nodes and data compression. The simulation results show that by using the proposed approach, the lifetime and the throughput of the network will be increased.

关键词： Wireless Sensor Network tree structure c4.5 algorithm data compression lifetim battery

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Nutritional Status of Infants classification by calculating Anthropometry Through c4.5 algorithm

Nutritional Status of Infants Classification by Calculating ...

引用

International conference on Electrical, Electronics and Information Engineering (IcEEIE)

作者： Wirawan, I. Made Widiyaningtyas, Triyanna Nurwakiah, Siti B. Univ Negeri Malang Dept Elect Engn Malang Indonesia Univ Negeri Malang Informat Engn Malang Indonesia

ISBN: (纸本)9781728141602

According to the research by Directorate General of Public Health, Ministry of Health Republic of Indonesia in 2015, a nutritional issue in Indonesia is still occurring. In accordance with the standard stipulated by WHO, ideally the prevalence of lean and short infants in certain area should be less than 25%. However, in Indonesia, 17.2% infants (0-60 months infants) have obese, lean, and very lean body compare to BB/U (weight index) index. A number of 29 % infants (0-60 months infants) have short and very short body compare to TB/U (height index) index. A number of 20.4% infants (0-60 months infants) are lack of nutrition or malnutrition. The stages of this research were (1) collecting data, (2) preprocessing data with data transformation, (3) classification process using c4.5 algorithm, and (4) evaluation testing results using c4.5 algorithm to calculate accuracy, precision, recall, and error rate through confusion matrix. Hence, in this research, the nutritional status of infants is classified according to Body Weight and Height indices using c4.5 algorithm. The results indicate that the average score of accuracy was 93.60% and the error rate was 6.40%.

关键词： c4.5 algorithm infants nutrition anthropometry

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A Method of Satellite Network Fault Synthetic Diagnosis Based on c4.5 algorithm and Expert Knowledge Database

A Method of Satellite Network Fault Synthetic Diagnosis Base...

引用

7th IEEE International conference on Wireless communications and Signal Processing (WcSP)

作者： Lin, Yusheng Ding, Shijie Wang, Yuqing Geng, Jizhao China Elect Technol Grp Corp Res Inst 54 Shijiazhuang Peoples R China

ISBN: (纸本)9781467376877

According to the actual need of fault location of satellite communication system, a fault synthetic diagnosis method based on c4.5 algorithm and expert knowledge database is proposed. The basic principle of c4.5 algorithm and expert knowledge database is discoursed. The process of building c4.5 fault diagnosis model and expert knowledge database is focused on and the implementation procedure of diagnosis process is described in detail.

关键词： Satellite Network Fault Diagnosis c4.5 algorithm Expert Knowledge Database

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An Online Software for Decision Tree classification and Visualization using c4.5 algorithm (ODTc)

An Online Software for Decision Tree Classification and Visu...

引用

8th International conference on computing for Sustainable Global Development (INDIAcom)

作者： Das, Suvajit Dahiya, Shashi Bharadwaj, Anshu IARI New Delhi India IASRI New Delhi India

ISBN: (纸本)9789380544120

classification is an important and widely carried out task of data mining. It is a predictive modelling task which is defined as building a model for the target variable as a function of the explanatory variables. There are many well established techniques for classification, while decision tree is a very important and popular technique from the machine learning domain. Decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs and utility. c4.5 is a well known decision tree algorithm used for classifying datasets. The c4.5 algorithm is Quinlan's extension of his own ID3 algorithm for decision tree classification. It induces decision trees and generates rules from datasets, which could contain categorical and/or numerical attributes. The rules could he used to predict categorical values of attributes from new records. c4.5 performs well in classifying the dataset as well as in generating useful rules. In this paper, a web based software for rule generation and decision tree induction using c4.5 algorithm has been discussed. The visualization in the form of tree structure enhances the understanding of the generated rules. The software contains the feature to impute the missing values in data. The input data can both he categorical and numerical in nature. The software can import TXT, XLS and cSV data file formats. Enhanced waterfall model has been used for the software development process. This software will he useful for academicians, researchers and students working in the area of data mining, agriculture and other fields where huge amount of data is generated.

关键词： c4.5 algorithm classification Data mining Decision Tree waterfall model

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Rainfall Forecasting in Bandung Regency using c4.5 algorithm 6

Rainfall Forecasting in Bandung Regency using C4.5 Algorithm

引用

6th International conference on Information and communication Technology (IcoIcT)

作者： Suyatno, Joko Azhari Nhita, Fhira Rohmawati, Aniq Atiqi Telkom Univ Computat Sci Bandung 40257 Indonesia

ISBN: (纸本)9781538645727

Bandung regency is one of Indonesian city that majority of the people are farmers. Farmers need weather information to determine the planting season. Weather forecasting become an orientation in agriculture sector to determining the beginning of planting season, and also quality and quantity of their harvest. One of the factors that affecting the harvest is rainfall. In this research, we make a classification model using c4.5 algorithm for rainfall forecasting at Bandung regency. Then, the postpruning method is used to optimize pruning on the model. We used a weather data from BMKG (Meteorological, climatological, and Geophysical Agency) in 2005 to 2016 period. The result of average accuracy testing without pruning is 60% and using pruning is 93.33%.

关键词： rainfall c4.5 algorithm pruning data mining

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