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检索条件"主题词=decision tree algorithm"

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Construction of a Student Learning Behavior Prediction Model Based on decision tree algorithm 24

Construction of a Student Learning Behavior Prediction Model...

引用

International Conference on Modeling, Natural Language Processing and Machine Learning (CMNM)

作者： Zhang, Guifang Wuhan Technol & Business Univ Wuhan 430065 Peoples R China

ISBN: (纸本)9798400709760

Diagnosis, monitoring, and evaluation of learning behavior have always been the focus of research in Educational Data Mining (EDM). Predicting student academic performance based on online learning behavior data for early intervention in student learning is a key issue that urgently needs to be addressed. The learning behavior of students can reflect the state of the learning process, the quality of teaching, and whether the school's management methods are good. Studying it can identify problems in educational work and propose corresponding solutions. This article constructs a student learning behavior prediction model based on decision tree (DT) algorithm. After reading data from the school data center, preprocessing is performed, and abnormal data is removed before DM and analysis. The results are obtained by comparing student behavior data with student grade points, providing more comprehensive support for university management services. The model can predict students' grades at the end of the course or predict whether they may face learning difficulties and require additional assistance. The experimental results indicate that the model proposed in this article helps to improve the learning effectiveness and experience of students, while also providing valuable teaching aids for teachers and educational institutions.

关键词： decision tree algorithm Student learning behavior prediction model

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Intrusion Detection System Using decision tree algorithm

Intrusion Detection System Using Decision Tree Algorithm

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14th IEEE International Conference on Communication Technology (ICCT)

作者： Kumar, Manish Hanumanthappa, M. Kumar, T. V. Suresh MS Ramaiah Inst Technol Dept Master Comp Applicat Bangalore 560054 Karnataka India Bangalore Univ Dept Comp Sci & Applicat Bangalore 560056 Karnataka India

ISBN: (纸本)9781467321013;9781467321006

Intrusion Detection System (IDS) is the most powerful system that can handle the intrusions of the computer environments by triggering alerts to make the analysts take actions to stop this intrusion. IDS's are based on the belief that an intruder's behavior will be noticeably different from that of a legitimate user. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious attacks by using traditional statistical methods to new data mining approaches in last decades. However, today's commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper we analyze a classification model for misuse and anomaly attack detection using decision tree algorithm.

关键词： Intrusion Detection System KDD Dataset Network Security decision tree algorithm

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Evaluating Information Technology Graduates Employability Using decision tree algorithm 18

Evaluating Information Technology Graduates Employability Us...

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9th International Conference on E-Education, E-Business, E-Management and E-Learning (IC4E)

作者： Tapado, Belen M. Acedo, Gemma G. Palaoag, Thelma D. Catanduanes State Univ Virac Catanduanes Philippines Univ Cordilleras Baguio Philippines

ISBN: (纸本)9781450354851

Employability of graduates reflects the quality of skills and competencies gained through a good quality of education provided by the academe that is suitable to the needs of the industry. It is also one of the performance indicators for the level of educational achievement of the tertiary institutions in the Philippines. Hence the importance of giving emphasis to the employability of graduates is imperative. This is the reason why this investigation is being conducted. Descriptive and Data Analysis method were employed in this research. A survey questionnaire was utilized as a data gathering tool to determine the data attributes and employable skills and competencies of the IT graduates. The answers to the questionnaires were tallied and were analyzed and classified using decision tree algorithm of Waikato Environment for Knowledge Analysis (WEKA) Version 3.9.1 wherein prescription of the common skills and competencies for each IT related jobs for IT graduates were obtained.

关键词： decision tree algorithm employability IT skills and competencies graduate tracer

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Application of decision tree algorithm in Lumber Hierarchies

Application of Decision Tree Algorithm in Lumber Hierarchies

引用

1st International Conference on Intelligent System and Applied Material (GSAM 2012)

作者： Guo, Dan Harbin Univ Commerce Sch Comp & Informat Engn Harbin Peoples R China

ISBN: (纸本)9783037853689

The decision tree algorithm is a kind of approximate discrete function value method with high precision, construction model of classification of noise data is simple and has good robustness etc, it is currently the most widely used in one of the inductive reasoning algorithms in data mining, extensive attention by researchers. This paper selects the decision tree ID3 algorithm to realize the standardization of lumber level division, to ensure the accuracy of the lumber division, while improving the partition of speed.

关键词： decision tree algorithm ID3 hierarchies

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The Construction of English New Words Corpus Based on decision tree algorithm 4th

The Construction of English New Words Corpus Based on Decisi...

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4th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences (MIND)

作者： Gao, Hongxia Beihua Univ Teachers Coll Jilin 132013 Jilin Peoples R China

ISBN: (纸本)9783031243516;9783031243523

An English word is a sound or a combination of sounds that we make with the vocal organs;words are representative, they represent some meaning, and they help humans communicate;words are part of the human language communication system. In short, words are the smallest and meaningful language units that humans can use independently. This paper aims to study the English neologism corpus based on decision tree algorithm. Aiming at the problems of low internal cohesion of words in the new word recognition algorithm of point mutual information and adjacency entropy, many high threshold invalid phrases and low threshold new phrases that exist in the single threshold setting of point mutual information, an improved multi-word point is proposed. A new word extraction algorithm for English of the year based on mutual information and adjacency entropy. In the preprocessing stage, according to the characteristics of English new words, it is further filtered, and the point mutual information is expanded into multi-word point mutual information, and the new words are extracted by setting double thresholds and adjacency entropy. In the recognition algorithm, this paper regards it as a classification problem to solve, analyzes English new words, and uses cosine similarity and path distance similarity to quantify word form and word meaning features. For phrase pairs containing acronyms, this paper An algorithm for identifying acronyms by rules is proposed, and a decision tree suitable for English new word recognition is constructed based on the features of word form and word meaning. Experiments show that the data of the algorithm in this paper is better than the traditional algorithm, the P value reaches 33.8%, and the accuracy rate is greatly improved. Compared with the word sense feature recognition algorithm, the method in this paper has a 4% improvement in accuracy.

关键词： decision tree algorithm Synonym Identification New Words New Word Corpus

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Teaching Reform of Financial Management Major in Applied Undergraduate Based on decision tree algorithm 17

Teaching Reform of Financial Management Major in Applied Und...

引用

17th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Xia, Juan Jiang, HaiYan HeBei Normal Univ Nationalities Business Sch Chengde City Hebei Peoples R China

ISBN: (纸本)9781728186160

With the continuous expansion of the enrollment scale of colleges and universities, the management of colleges and universities is becoming more and more difficult, and the corresponding data accumulation is also more and more. The key to the development of colleges and universities is to analyze the factors affecting the cultivation of students and improve the methods of students' training. According to the teaching data of colleges and universities, we can use the data mining technology to transform the existing teacher management data into useful information, and through data analysis to explore the internal factors affecting students' academic performance, so as to provide theoretical guidance for improving teaching methods. The results show that in order to improve the level of education and training in Colleges and universities, it is necessary to analyze the teaching quality of financial management course according to the needs of teaching. In order to optimize the course testing link, improve teaching methods and do a good job in teaching evaluation. We can guide the adjustment of students' cultural theory and practice courses through the analysis of students' performance data, and determine a reasonable student training program. This paper proposes to use decision tree algorithm to generate effective information to help managers to make decisions and financial budget management, so as to carry out experiments.

关键词： decision tree algorithm Financial Management Teaching Reform Application Research

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Application of Birth Defect Prediction Model Based on C5.0 decision tree algorithm 11

Application of Birth Defect Prediction Model Based on C5.0 D...

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IEEE International Congress on Cybermatics / IEEE Conferences on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology

作者： Guo, Junmei Liu, Haiying Luan, Yizhong Wu, Yun Qilu Univ Technol Shandong Acad Sci Sch Elect Engn & Automat Jinan 250353 Shandong Peoples R China Shandong Univ Inst Marine Sci & Technol Jinan 250061 Shandong Peoples R China Guizhou Univ Coll Comp Sci & Technol Guiyang 550000 Guizhou Peoples R China

ISBN: (纸本)9781538679753

As newborn children commonly suffer from diseases, birth defects have become a problem of social concern. Birth defect is not only the key cause of childhood disease, but also the main factor of child death. In this paper, the birth defect prediction model is applied in this paper based on the principle of decision tree classification and prediction algorithm. Firstly, the theory of C5.0 decision tree algorithm is expounded. Secondly, the data of birth defect prediction model is analyzed and designed. Then, the performance of C4.5 algorithm and C5.0 algorithm is compared. Finally, the C5.0 decision tree algorithm is selected to construct the prediction model of birth defect. The result shows that the C5.0 decision tree algorithm has good predictive value for birth defect prediction model.

关键词： Birth defect decision tree algorithm Prediction algorithm

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A Study on the Application of the decision tree algorithm in Psychological Information of Vocational College Students

A Study on the Application of the Decision Tree Algorithm in...

引用

International Conference on Engineering Technology and Application (ICETA)

作者： Cheng, Dongmei Li, Tan Niu, Lihua Langfang Hlth Vocat Coll Dept Publ Basic Langfang Hebei Peoples R China

This paper discusses the basic operating principle and the development status of data mining technology, analyzes the insufficiency of the existing psychological management system, and proposes the development trend of psychological health education in colleges. According to an analysis on factors affecting college students' mental health and the deviation between the reality and the current number of students with psychological abnormality, this paper studies the application of data mining technology and puts forward a system based on data mining that combines the classified data mining technology with the existing psychological management system.

关键词： decision tree algorithm psychological information of college students data mining

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A NOVEL METHOD of TRANSFORMER FAULT DIAGNOSIS BASED on K-MEDIODS and decision tree algorithm 1

A NOVEL METHOD of TRANSFORMER FAULT DIAGNOSIS BASED on K-MED...

引用

1st International Conference on Electrical Materials and Power Equipment (ICEMPE)

作者： Zhou, Zhou Si, Gangquan Chen, Jiaxi Zheng, Kai Yue, Wenmeng Xi An Jiao Tong Univ Sch Elect Engn State Key Lab Elect Insulat & Power Equipment Xian Shaanxi Peoples R China

ISBN: (纸本)9781509057368

Served as one of the main method to construct the artificial intelligence system, decision tree algorithm has been proved to be an effectiveness way to imitate the decision process of human. In the research of its application, some scholars focus on the characteristic of data to build the decision tree. They repute that minimizing the amount of training data before constructing can improve the performance of the algorithm compared to simplifying the decision tree after generated, that is, using the pre-processing technology. Based on the idea, this work proposes a new decision tree method based on k-mediods and ID3, and applies it to transformer fault diagnosis. The method first uses k-mediods algorithm to extract the representative training data from data-set of oil chromatographic failure, and then it runs decision tree algorithm to build the decision tree. Finally, the tree could be applied for fault diagnosing. The preliminary experimental results show that, the method could reduce the complexity of the decision tree and enhance the decision performance.

关键词： Transformer fault diagnosis Operational evaluation K-mediods algorithm decision tree algorithm

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Regional Voltage Stability Prediction based on decision tree algorithm

Regional Voltage Stability Prediction based on decision tree...

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International Conference on Intelligent Transportation, Big Data and Smart City (ICITBS)

作者： Teng Yun Huo Tengyu Liu Bing Tang Jing Zhang Zhongjie Shenyang Univ Technol Minist Educ Key Lab Special Elect Machine & High Voltage Appa Shenyang 110870 Liaoning Provin Peoples R China State Grid Tongliao Power Supply Co Tongliao 028000 Inner Mongolia Peoples R China

ISBN: (纸本)9781509004645

Because of the imperfection of the theory concerning the regional dynamic and static voltage stability evaluation problem and insufficient reliability of the history data retrieved from the FTU, a novel pattern-recognition based algorithm is proposed. The proposed algorithm utilizes advantage of the decision tree algorithm and a decision tree algorithm model was built for the purpose of evaluation of voltage stability status of the regional power grid. Three feature has been extracted for the recognition of the instability pattern. The training set and the test set data are both obtained from simulation data and outputs. By using the proposed method on IEEE 39-bus system and the predefined critical unstable situations, we obtained the decision tree algorithm model on the IEEE 39-bus system stability prediction model. After the simulation, the output data are compared with the original stability status. The experiment comparison shows that the decision tree algorithm model has achieved the acceptable accuracy for the assessment of voltage stability prediction of the regional power grid. The validity of the proposed assessment scheme as well as the adaptability and the accuracy of the classification model are verified by simulation results of IEEE 39-bus system..

关键词： decision tree algorithm Voltage stability IEEE 39-bus system Feature Extraction

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