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Grid pattern recognition in road networks using the c4.5 algorithm

cARTOGRAPHY AND GEOGRAPHIc INFORMATION ScIENcE 2016年第3期43卷 266-282页

作者： Tian, Jing Song, Zihan Gao, Fei Zhao, Feng Wuhan Univ Sch Resource & Environm Sci Wuhan 430072 Peoples R China Wuhan Univ Key Lab Geog Informat Syst Minist Educ Wuhan 430072 Peoples R China

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh's individual characteristics and spatial context. The classifier is generated using the c4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.

关键词： Road network grid pattern supervised learning c4.5 algorithm classification

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Implementation of c4.5 algorithm to Determine Hospital Readmission Rate of Diabetes Patient 4

Implementation of C4.5 Algorithm to Determine Hospital Readm...

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4th International conference on New Media Studies (cONMEDIA)

作者： Tamin, Felix Iswari, Ni Made Satvika Univ Multimedia Nusantara Fac Engn & Informat Tangerang Indonesia

ISBN: (纸本)9781509062843

Diabetes is a disease in which the body's ability to produce or respond to the hormone insulin is impaired, resulting in abnormal metabolism of carbohydrates and elevated levels of glucose in the blood and urine. It can be suffered by everyone and until now there is no cure for it. A hospital readmission is an episode when a patient who had been discharged from a hospital is admitted again within a specified time interval. Readmission rates have increasingly been used as a quality benchmark for health systems. In this research, c.45 algorithm is used to determine hospital readmission rate of diabetes patient. Dataset used in this study is taken from UcI Machine Learning Repository, which contain diabetic patient data from 130 hospitals in United States for 10 years (1999-2008). Several experiments are done to get the best result, and the best result is 74.5% for accuracy. This result is obtained by doing several preprocess data i.e. filling all missing value, using numeric and nominal attribute type, and by not including several attributes.

关键词： c4.5 algorithm decision tree diabetes readmission data mining

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The Analysis and Application of the c4.5 algorithm in Decision Tree Technology

The Analysis and Application of the C4.5 Algorithm in Decisi...

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International conference on Advanced Materials and Engineering Materials (IcAMEM 2011)

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

ISBN: (纸本)9783037853559

The Decision Tree technology, which is the main technology of the Data Mining classification and forecast, is the classifying rule that infers the Decision Tree manifestation through group of out-of-orders, the non-rule examples. Based on the research background of The Decision Tree's concept, the c4.5 algorithm and the construction of The Decision Tree, the using of c4.5 Decision Tree algorithm was applied to result analysis of students' score for the purpose of improving the teaching quality.

关键词： Data Mining Decision Tree c4.5 algorithm Score Analysis

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customer Loyalty Prediction In Multimedia Service Provider company With K-Means Segmentation And c4.5 algorithm 1

Customer Loyalty Prediction In Multimedia Service Provider C...

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1st International conference on Informatics and computing (IcIc)

作者： Moedjiono, Sardjoeni Isak, Yosianus Robertus Kusdaryono, Aries Budi Luhur Univ Jakarta Indonesia

ISBN: (纸本)9781509016488

The development needs the internet and cable television entertainment increase per year that affect popping up various multimedia service provider company which is offered a lot of services to win the market. This makes customer has a lot of company choices and makes customer to be more demanded and move easily from a provider to other provider, where company knows that keep customer has the cost that is lower than the cost to get new customer. So, it's important for company to know customer loyalty and company can also project the income as reference in company development planning. company needs to has accurate model, so researcher uses k-means segmentation and c4.5 classification algorithm, which can be seen that the model has accuracy 79.33% and Area Under curve (AUc) 0.831. This research contribution is the use of related data using customer potential segmentation based on Recency Frequency Monetary (RFM) model, so can increase accuracy percentage in customer loyalty classification research.

关键词： c4.5 algorithm customer loyalty K-means algorithm multimedia company prediction

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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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Research on c4.5 algorithm improvement strategy based on MapReduce 10

Research on C4.5 algorithm improvement strategy based on Map...

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10th Annual International conference of Information and communication Technology (IcIcT)

作者： Wang, Huan-Bin Gao, Yang-Jun Airforce Engn Univ Coll Equipment Management & Unmanned Aerial Vehic Xian 710051 Shanxi Peoples R China

By analyzing the shortcomings of c4.5 decision tree algorithm, this paper combines MapReduce parallel model in Hadoop platform with c4.5 decision tree algorithm, so that c4.5 algorithm can be executed in parallel, so as to improve the efficiency of the algorithm. The improved c4.5 algorithm implementation process is given and the process is analyzed. Finally, the c4.5 algorithm improved experimental environment configuration is explained. (c) 2021 The Authors. Published by Elsevier B.V.

关键词： MapReduce Data mining c4.5 algorithm Parallelization

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The Improvement of c4.5 algorithm and case Study

The Improvement of C4.5 Algorithm and Case Study

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2nd International Symposium on computational Intelligence and Design

作者： Li Rui Wei Xian-mei Yu Xue-wei Dalian Jiaotong Univ Software Inst Dalian Peoples R China

ISBN: (纸本)9780769538655

The paper introduces a balanced coefficient to improve the veracity of c4.5 algorithm. It can be fixed by decision maker according to priori intellectual and domain intellectual. It harmonized the information gain-ratio of each attributes artificially in specific environment. The classification is more veracious and rational by the decision tree made from the improved algorithm. And compared the improved algorithm to c4.5 algorithm by analyzing examples, to prove the efficiency of the improved algorithm.

关键词： classification of data Decision tree c4.5 algorithm Degree of balance coefficient

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Design of Decision Support System with c4.5 algorithm Methods in Determining Results Vaname Shrimp cultivation 5

Design of Decision Support System with C4.5 Algorithm Method...

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5th International conference on New Media Studies (cONMEDIA)

作者： Tobing, Fenina Adline Twince Dzulhaq, Muhammad Iqbal Overbeek, Marlinda Vasty Setiawan, Eko Anto Univ Multimedia Nusantara Informat Dept Fac Tech & Informat Tangerang Banten Indonesia STMIK Bina Sarana Global Informat Tech Depatrment Tangerang Banten Indonesia

ISBN: (纸本)9781728107264

Water quality has a very important role in the success of shrimp farming. Water as a living medium for shrimp, has a direct effect on the health and growth of shrimp. Water quality determines the existence of various types of organisms in the pond ecosystem, both for shrimp and other biota. Water quality that is far from the optimal value can cause cultivation failure, while optimal water quality can support shrimp growth. This study aims to build a decision support system to help companies manage water quality to get good shrimp farming results. The attributes used are water height, salinity, DO, pH, temperature, alkalinity and target size attributes of shrimp. The data used were 93 data partitioned into 76 training data and 17 testing data. Based on the classification results using the c4.5 algorithm, accuracy was 76.47%, precision was 72.72% and recall was 88.88%. From this study it was proven that the decision support system with the c4.5 algorithm can be used to determine the results of vaname shrimp farming.

关键词： Shrimp cultivation Decision Support System c4.5 algorithm

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classification Method of Multi-class on c4.5 algorithm for Fish Diseases 2

Classification Method of Multi-class on C4.5 Algorithm for F...

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2nd International conference on Science in Information Technology (IcSITech)

作者： Sucipto Kusrini Taufiq, Emha Luthfi STMIK AMIKOM Yogyakarta Informat Engn Yogyakarta Indonesia

ISBN: (纸本)9781509017218

The background of the research is to analyze data derived from an elucidation of catfish and carp diseases in Kediri, East Java, Indonesia. The research shows that data about fish's disease history have not been used effectively because it is only be collected. Data about fish's symptom history used by fish trainer only present the number of fish that get disease. Data about fish's history should be also optimized to discover the relationship among fish's disease. Thus, anticipation about disease that always attack fish could be prevented earlier. The research is done to understand the relationship history among fish's disease. Then the accuracy of relationship quality is measured to acquire the quality of data properly so it can be worked to identify fish's disease. Data relationship quality among fish's disease symptoms should be understood to know how is the accuracy of datum classification obtained. A proper method is required to extract information from data obtained. There are many data-mining classification algorithms such as cART, cHAID, Rain Forest, and c4.5. But, the c4.5 algorithm is appropriate for this research used to form decision tree for data quality assessed from accurate performance of some multi-class fish diseases. This research uses 1120 data involving six diseases. The data were obtained from Agriculture Board (fishery subdivision) of Kediri Regency. The result shows that c4.5 algorithm is well to do for both a low and high accuracy class at 55.3 and 88.4 percent.

关键词： classification c4.5 algorithm multi-class

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Analysis of Students Graduation Target Based on Academic Data Record Using c4.5 algorithm case Study: Information Systems Students of Telkom University 6

Analysis of Students Graduation Target Based on Academic Dat...

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

作者： Putri, Dela Youlina Andreswari, Rachmadita Hasibuan, Muhammad Azani Telkom Univ Sch Ind Engn Study Program Informat Syst Jl Telekomunikasi 01 Bandung 40257 West Java Indonesia

ISBN: (纸本)9781538654330

Study program of Information Systems is one of the existing study programs at Telkom University which has produced many graduates until 2017. However, not all graduates produced successfully completed the study period during four years of normal study period in which may cause the decrease of study programs quality and affect the assessment of study program if there is an audit or evaluation so it can affect the achievement level of the study program. To solve the problem can be by making a prediction model of student graduation that can be obtained from data classification process using decision tree with algorithm c4.5 and implement it to the academic data record of existing student so that got two group of student, that is student which predicted pass on time and student predicted to pass late. From the results of the classification of student data can be done an analysis of what factors that can affect the graduation of students who are predicted to pass on time and plan appropriate strategies for groups of students who may not pass on time. The data classification process is done with the help of open source based tools using RapidMiner application. The result of the classification is a prediction model that has an accuracy value of 82.24% and states that the most influential factor in predicting students' graduation is GPA in the second year. The result of the student's graduation classification is expected to be used as the reference base to support the academic planner in making the right decision to the student groups generated so that all students can graduate on time.

关键词： student passing prediction data classification decision tree c4.5 algorithm RapidMiner

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