检索结果-内蒙古大学图书馆

6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

作者： Hsu, Ting-Chia Zhou, Kai-Zhong Natl Taiwan Normal Univ Dept Technol Applicat & Human Resource Dev Taipei Taiwan

ISBN: (纸本)9781538606216

This study proposes a recommendation system for video clips based on the id3 algorithm. The system was developed using the Python programming language. There were totally seven videos instructing how to design a webpage. The videos were micro lectures, so the length of each was only 10 minutes for each learning unit. When the system diagnoses the prior knowledge of the students, the recommendation system will decide the starting learning node for the individual students. The system was used in remedial instruction of webpage design. The system checked which individual students' weaknesses required strengthening after one round of self-learning. The results showed that the remedial instruction recommended by the system was successful enough to significantly improve the students' learning effectiveness. The results indicated that the self-efficacy of the low-achievement students achieved a level as high as that of the high-achievement students after the students employed the proposed approach to enhancing their webpage design learning and received the required learning videos. Because the low-achievement students received more remedial instruction learning materials, they had higher external cognitive loads. However, because the difficulty level of the learning materials which were recommended to the individuals conformed to their prior knowledge, the internal cognitive loads of the high achievement students were not significantly different from those of the low-achievement students.

关键词： recommendation system remedial instruction self-efficacy cognitive load id3 algorithm

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Generating Decision Trees Method Based on Improved id3 algorithm

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China Communications 2011年第5期8卷 151-156页

作者：杨明郭树旭王隽 College of Electronic Science & Engineering Jilin University Department of Management Information System China Mobile Communications Corporation Department of Special Assets Resolution China Construction Bank

The id3 algorithm is a classical learning algorithm of decision tree in data *** algorithm trends to choosing the attribute with more values,affect the efficiency of classification and prediction for building a decision *** article proposes a new approach based on an improved id3 *** new algorithm introduces the importance factor λ when calculating the information *** can strengthen the label of important attributes of a tree and reduce the label of non-important *** algorithm overcomes the flaw of the traditional id3 algorithm which tends to choose the attributes with more values,and also improves the efficiency and flexibility in the process of generating decision trees.

关键词： decision tree id3 algorithm importance factor attribute value

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Producing Security Policy of IPSec Based on Improved λ-id3 algorithm

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JOURNAL OF INTERNET TECHNOLOGY 2012年第1期13卷 19-26页

作者： Yang, Ming Guo, Shuxu Wang, Jun Jilin Univ Coll Elect Sci & Engn Changchun Jilin Province Peoples R China

IPSec is a policy-driven security mechanism. How to quickly generate corresponding security policy due to the diversity of network security is one of the core issues of IPSec. Although IPSec supports a rich set of protection modes and operations, its policy configuration remains an inefficient and error-prone task in the dynamic conditions. In this article, we propose an IPSec policy engine which can generate dynamically and store the security policy of IPSec under different algorithms. Furthermore, we extend a novel id3 algorithm to automatically generate correct policies. The algorithm, which introduces the dynamic parameter - importance factor lambda when calculating the information entropy, can overcome the flaw of traditional id3 algorithm that tends to choose attributes that have more values, and improve the efficiency and flexibility of IPSec security policy, and better meet the actual situation.

关键词： IPSec Security policy id3 algorithm Policy engine Importance factor

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College English Network Independent Learning Based on id3 algorithm

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AGRO FOOD INDUSTRY HI-TECH 2017年第1期28卷 3342-3345页

作者： Wang, Li Tianjin Chengjian Univ Sch Foreign Lanuguage Tianjin Peoples R China

The rapid development of internet transferred college students' traditional offline learning into network independent learning, which, however, still developed slowly. This paper intends to analyze college student's network independent learning with id3 algorithm, showing the effectiveness and simplicity of id3 algorithm by survey and analysis, which could not only produce accurate results, but also analyze the process. Thus, id3 algorithm proved the availability of network independent English learning, as well as promoted the subjective initiative of students.

关键词： id3 algorithm college students' English network independent learning

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Breast cancer disease classification using fuzzy-id3 algorithm with FUZZYDBD method: automatic fuzzy database definition

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PEERJ COMPUTER SCIENCE 2021年 7卷 e427页

作者： idris, Nur Farahaina Ismail, Mohd Arfian Univ Malaysia Pahang Coll Comp & Appl Sci Fac Comp Pekan Pahang Malaysia

Breast cancer becomes the second major cause of death among women cancer patients worldwide. Based on research conducted in 2019, there are approximately 250,000 women across the United States diagnosed with invasive breast cancer each year. The prevention of breast cancer remains a challenge in the current world as the growth of breast cancer cells is a multistep process that involves multiple cell types. Early diagnosis and detection of breast cancer are among the greatest approaches to preventing cancer from spreading and increasing the survival rate. For more accurate and fast detection of breast cancer disease, automatic diagnostic methods are applied to conduct the breast cancer diagnosis. This paper proposed the fuzzy-id3 (Fid3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. This study aims to resolve the limitation of an existing method, id3 algorithm that unable to classify the continuous-valued data and increase the classification accuracy of the decision tree. Fid3 algorithm combined the fuzzy system and decision tree techniques with id3 algorithm as the decision tree learning. FUZZYDBD method, an automatic fuzzy database definition method, would be used to design the fuzzy database for fuzzification of data in the Fid3 algorithm. It was used to generate a predefined fuzzy database before the generation of the fuzzy rule base. The fuzzified dataset was applied in Fid3 algorithm, which is the fuzzy version of the id3 algorithm. The inference system of Fid3 algorithm is simple with direct extraction of rules from generated tree to determine the classes for the new input instances. This study also analysed the results using three breast cancer datasets: WBCD (Original), WDBC (Diagnostic) and Coimbra. Furthermore, the comparison of Fid3 algorithm with the existing methods is conducted to verify the proposed method's capability and performance. This study identified that the combination of Fid3 algorithm with FUZZYDBD

关键词： Fuzzy id3 algorithm Fid3 algorithm Fuzzy decision tree FUZZYDBD Breast cancer Classification Fuzzification

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Improvement of id3 algorithm Based on Simplified Information Entropy and Coordination Degree

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algorithmS 2017年第4期10卷 124-124页

作者： Wang, Yingying Li, Yibin Song, Yong Rong, Xuewen Zhang, Shuaishuai Shandong Univ Sch Control Sci & Engn Jinan 250061 Shandong Peoples R China Shandong Univ Sch Mech Elect & Informat Engn Weihai 264209 Peoples R China Shandong Univ Sci & Technol Dept Elect Engn & Informat Technol Jinan 250031 Shandong Peoples R China

The decision tree algorithm is a core technology in data classification mining, and id3 (Iterative Dichotomiser 3) algorithm is a famous one, which has achieved good results in the field of classification mining. Nevertheless, there exist some disadvantages of id3 such as attributes biasing multi-values, high complexity, large scales, etc. In this paper, an improved id3 algorithm is proposed that combines the simplified information entropy based on different weights with coordination degree in rough set theory. The traditional id3 algorithm and the proposed one are fairly compared by using three common data samples as well as the decision tree classifiers. It is shown that the proposed algorithm has a better performance in the running time and tree structure, but not in accuracy than the id3 algorithm, for the first two sample sets, which are small. For the third sample set that is large, the proposed algorithm improves the id3 algorithm for all of the running time, tree structure and accuracy. The experimental results show that the proposed algorithm is effective and viable.

关键词： decision tree id3 algorithm information entropy coordination degree

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Improved id3 algorithm

Improved ID3 Algorithm

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2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Liu Yuxun College of Information Science and Engineering Henan University of Technology Zhengzhou,China Xie Niuniu College of Information Science and Engineering Henan University of Technology Zhengzhou,China

as the classical algorithm of the decision tree classification algorithm,id3 is famous for the merits of high classifying speed easy,strong learning ability and easy *** when use it to classify,there does exist the problem of inclining to chose attributions which has many values,which affects its *** paper for solving the problem a decision tree algorithm based on attribute- importance is *** improved algorithm uses attribute-importance to increase information gain of attribution which has fewer attributions and compares id3 with improved id3 by an *** experimental analysis of the data show that the improved id3 algorithm can get more reasonable and more effective rules

关键词： decision tree id3 algorithm attribute-importance

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A Game AI based on id3 algorithm

A Game AI based on ID3 Algorithm

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International Conference on Contemporary Computing and Informatics

作者： Yang Li Dai-Wen Xu School of Electronic Science and Applied Physics HeFei University of Technology

ISBN: (纸本)9781509052578

Traditional game AI is aimed at the standard players in the beginning of the construction. After designing the AI, The whole game decision-making system will not be dynamically adjusted, Because of the strong regularity, the traditional game AI is easy to be found the weakness by users, which is not easy to maintain the rationality of the decision. This paper presents a design scheme of game AI based on decision tree algorithm id3. It through the mining of the player with the NPC interactive data on the set target has a significant correlation of data clues, real-time control of the decision-making system, to maintain the rationality of the decision. The experimental results show that the proposed scheme can adapt to the player's operation well, and it can keep the rationality of the decision in the actual operating environment.

关键词： Artificial intelligence Behavior tree id3 algorithm Decision tree Game AI Non-player character

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The Analysis and Optimization of Decision Tree Based on id3 algorithm

The Analysis and Optimization of Decision Tree Based on ID3 ...

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2017 9th International Conference on Modelling, identification and Control (ICMIC 2017)

作者： He Zhang Runjing Zhou the College of Electronic Information of Inner Mongolia University

Decision tree is one of the complex algorithms in the fields of pattern recognition and data mining,which is not only related to database,artificial intelligence and other disciplines,but has great theoretical research *** paper used standard data set as original discrete experimental data,and the entropy and information gain of each attribute of the data was calculated to implement the classification of *** traversing the structure of tree,the attributes corresponding to the information gain that reduces the maximum entropy were selected as optimal classification attribute for the generation of the decision *** simulation results show that the classification accuracy of id3 decision tree was 6-7 percentage points higher than the other classification algorithms in this paper,meanwhile,the generation of the tree structure was apparently *** addition,this paper achieved an optimized structure of the decision tree,which is simplified to 5 node structure from the initial 19 nodes for improving the efficiency of the algorithm on the premise of ensuring low error rate which was at the same level as other classification algorithms.

关键词： id3 algorithm Decision Tree Structural Optimization Data Mining Pattern Recognition

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Diagnosis of Hepatitis C Virus Based on id3 algorithm

Diagnosis of Hepatitis C Virus Based on ID3 Algorithm

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作者： Yue Che Dalian Maritime University

Infection with the hepatitis C virus(HCV) is what causes hepatitis *** has one of the highest hepatitis C infection rates in the world(13%-15%),and this illness affects more than 170 million people *** a result,there is an enormous need for the diagnosis of this *** recent years,researchers have made significant progress in this field with different machine learning algorithms and have had the ability to make a relatively precise ***,within the machine learning algorithms that the researchers used,decision trees,particularly the id3(Iterative Dichotomiser 3) algorithm,have been *** paper uses this algorithm in the diagnosis of hepatitis C,aiming to test the accuracy and explore the possibility of introducing this approach into application in ***,the novel method of applying the id3 algorithm in the diagnosis of hepatitis C can produce relatively accurate results compared with those traditional approaches,demonstrating that this method can be used in practice and is a powerful approach for diagnosing people who have the hepatitis C virus.

关键词： Hepatitis C Machine learning id3 algorithm Decision Tree

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