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检索条件"主题词=Decision Tree Algorithm"

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A Critical Study of Classification algorithms Using Diabetes Diagnosis 6

A Critical Study of Classification Algorithms Using Diabetes...

引用

IEEE 6th International Advance Computing Conference (IACC)

作者： Srikanth, Panigrahi Deverapalli, Dharmaiah VNR VJIET Dept Informat Technol Hyderabad Telagana India Shri Vishnu Engn Coll Woman Dept Informat Technol Bhimavaram India

ISBN: (纸本)9781467382861

This paper predicts the Diabetes Disease based on Data Mining Techniques of Classification algorithms. Classification algorithm and tools may reduce heavy work on Doctors. In this paper Evaluated as Classification algorithms for the Classify of some Diabetes Disease Patient Datasets. Data Mining is one of the main algorithm is Classification. Classification algorithm Examine of the decision tree algorithm, Byes algorithm and Rule based algorithm. These algorithms are evaluate Error Rates and identify of the patients based evolution Function of the measure the accurate results.

关键词： Pima Diabetes Disease Data set Classification algorithm decision tree algorithm Byes algorithms and Rules

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Improving Arabic Text Categorization using decision trees

Improving Arabic Text Categorization using Decision Trees

引用

1st International Conference on Networked Digital Technologies (NDT 2009)

作者： Harrag, Fouzi El-Qawasmeh, Eyas Pichappan, Pit Farhat ABBAS Univ Dept Comp Sci Setif 19000 Algeria JUST Univ Comp Sci Dept Amman 25000 Jordan Al Imam Univ Dept Comp Sci Riyadh Saudi Arabia

ISBN: (纸本)9781424446148

This paper presents the results of classiying Arabic text documents using a decision tree algorithm. Experiments are performed over two self collected data corpus and the results show that the suggested hybrid approach of Document Frequency Thresholding using an embedded information gain criterion of the decision tree algorithm is the preferable feature selection criterion. The study concluded that the effectiveness of the improved classifier is very good and gives generalization accuracy about 0.93 for the scientific corpus and 0.91 for the literary corpus and we also conclude that the effectiveness of the decision tree classifier was increased as we increase the training size, and the nature of the corpus has such a influence on the classifier performance.

关键词： Text Mining decision tree algorithm Text Categorization Arabic Corpus Feature Selection

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Detecting Pantana Phyllostachysae Using GF-2 Images 2

Detecting Pantana Phyllostachysae Using GF-2 Images

引用

2nd International Conference on Frontiers of Sensors Technologies (ICFST)

作者： Wu, Hongzhi Yang, Dong Shao, Bo Qiao, Rui Sun, Linwen Shi, Feng Shandong Inst Dev Strategy Sci & Technol Jinan Shandong Peoples R China Univ Waterloo Dept Math Waterloo ON Canada

ISBN: (纸本)9781509048601

Forest disturbances caused by Pantana phyllostachysae caused the death of extensive bamboos in Hubei province, China in 2015. Field survey is time-consuming and at higher cost to satisfy the forest management requirements. Satellite remote sensing technology having the characteristics of landscape of coverage, convenient, and fast in formation acquisition, is one of the most important and most effective ways of discriminating the damage. Based on decision tree algorithm, the study compared the results on the condition of segmentation variables on different scales and colors and proposed that GF-2 image are suitable for discriminating the damage as an alternative of field survey.

关键词： GF2 image decision tree algorithm detection

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Focused Deep Web Entrance Crawling by Form Feature Classification 1st

Focused Deep Web Entrance Crawling by Form Feature Classific...

引用

1st International Conference on Big Data Computing and Communications (BigCom)

作者： Wang, Lin Hawbani, Ammar Wang, Xingfu Univ Sci & Technol China Comp Sci & Technol Hefei 230022 Anhui Peoples R China

ISBN: (纸本)9783319220475;9783319220468

Currently, Most back-end web databases cannot be indexed by traditional hyperlink-based search engines due to their requirement of users' interactive queries via page form submission. In order to make hidden-Web information more easily accessible, this paper proposes a hierarchical classifier to locate domain-specific hidden Web entries at a large scale. The classifier is trained by appropriately selected page form features to get rid of non-relevant domains and non-searchable forms. Experiments conducted on eight different topics demonstrate that the technique can discover deep web interfaces accurately and efficiently.

关键词： Deep web Focused crawler Searchable forms HTML analysis SVM classifier decision tree algorithm

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Fast Numerical Threshold Search algorithm for C4.5 3

Fast Numerical Threshold Search Algorithm for C4.5

引用

3rd IIAI International Conference on Advanced Applied Informatics (IIAI-AAI)

作者： Chong, Wen-Mau Goh, Chien-Le Bau, Yoon-Teck Lee, Kian-Chin Multimedia Univ Fac Comp & Informat Cyberjaya Malaysia

ISBN: (纸本)9781479941735

This paper presents a new algorithm to improve the speed of threshold searching process in C4.5 by using the technique of genetic algorithms. In the threshold searching process in C4.5, the values in a numerical attribute are sorted first and then the mid-point between every two consecutive values is calculated and designated as a candidate threshold. This process can be time consuming and it is not practical for large data. Our algorithm generates a population of possible thresholds and converges to the best threshold value rapidly. Our experimental results have shown that significant time reduction has been achieved by using our algorithm in threshold searching process.

关键词： classification decision tree algorithm numerical attribute genetic algorithm

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Modeling and control of a hybrid PV-T collector using machine learning 31

Modeling and control of a hybrid PV-T collector using machin...

引用

31st Mediterranean Conference on Control and Automation (MED)

作者： Ul Abdin, Zain Rachid, Ahmed Univ Picardie Jules Verne Lab Technol Innovantes F-80000 Amiens France

ISBN: (纸本)9798350315431

Photovoltaic-thermal (PV-T) systems are expected to fulfil an increasingly vital role in future energy production. The current research endeavors to showcase machine learning modeling and control of a water-based PV-T collector. In this work, the PV-T collector is modeled using a decision tree algorithm and artificial neural network (ANN). The predicted outputs are compared with the actual outputs to validate the models. The ANN-based model performed better and proved its efficacy in training and testing. Further, various control strategies are implemented and their performance is compared. All the techniques presented are illustrated through simulation results.

关键词： PV-T collector modeling decision tree algorithm artificial neural network control

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Improvement of ID3 algorithm Based on Simplified Information Entropy and Coordination Degree

Improvement of ID3 Algorithm Based on Simplified Information...

引用

Chinese Automation Congress (CAC)

作者： Wang Ying-ying Li Yi-bin Rong Xue-wen Shandong Univ Sch Control Sci & Engn Jinan 250061 Shandong Peoples R China Shandong Univ Jinan Shandong Peoples R China

ISBN: (纸本)9781538635247

In data classification mining, the decision tree method is a key algorithm. ID3 (Iterative Dichotomiser 3) algorithm which was presented by Quinlan is a famous decision tree algorithms, but ID3 has some shortcomings such as high complex computation in computing the information entropy expression, multivalue bios problem in the process of selecting an optimal attribute, large scales, etc. In order to solve the above problems, the improved ID3 algorithm is proposed, which combines the simplified information entropy with coordination degree in rough set theory. The experiment result has proved the feasibility of the optimized way.

关键词： decision tree algorithm ID3 algorithm information entropy coordination degree

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Water Bloom Warning Model Based on Random Forest 2

Water Bloom Warning Model Based on Random Forest

引用

2nd International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)

作者： Liu, Yunxiang Wu, Hao Shanghai Inst Technol Sch Comp Sci & Informat Engn Shanghai Peoples R China

ISBN: (纸本)9781509066643

Based on the random forest classification algorithm, a warning model of water bloom is proposed. Using the collected data, Select the water quality, meteorological factors which like Chlorophyll a (Chl-a), water temperature (T), PH, nitrogen and phosphorus ratio (TN: TP), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), dissolved oxygen Light (E) and so on as the impact factor and use them establish a warning model for Water bloom. And compared with the prediction accuracy of neural network model and SVM model. The results show that the water bloom warning model is established by using stochastic forest classification algorithm, the prediction accuracy is slightly higher than other algorithms. And the random forest algorithm has the characteristics of high robustness, China good performance, strong practicability, can effectively carry out water bloom early warning.

关键词： Random forest decision tree algorithm water bloom warning split attribute set

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Effect of increased number of COVID-19 tests using supervised machine learning models

Effect of increased number of COVID-19 tests using supervise...

引用

Australian and New Zealand Control Conference (ANZCC)

作者： Pooja, W. Snehal, N. Sonam, K. Wagh, S. R. Singh, N. M. VJTI EED Control & Decis Res Ctr CDRC Mumbai Maharashtra India

ISBN: (纸本)9781665416504

Machine learning is widely being used in medical field for disease diagnostics and *** area of machine learning is mainly classified into 3 parts: supervised, unsupervised and reinforcement *** machine learning (ML) algorithms are used in this paper for modeling and showing the impact of increased testing on the number of daily confirmed cases of COVID-19. The algorithms used to carry out this study are decision tree regression and random forest regression. Machine learning for modeling has proven to be significant for forecasting and hence decision making over the future course of actions. In this paper, Gaussian process regression has been used for modeling as well as forecasting the daily confirmed cases in South Korea. The results obtained show that if the number of tests conducted is increased to the population of South Korea, approximately equal to 51, 286, 183, the peak in the daily cases is obtained earlier and hence the overall number of daily cases is less compared to current cases.

关键词： COVID 19 decision tree algorithm Gaussian process regression machine learning random forest algorithm

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Privacy Threats from Social Networking Service Aggregators 5

Privacy Threats from Social Networking Service Aggregators

引用

5th Cybercrime and Trustworthy Computing Conference CTC

作者： Jaafor, Omar Birregah, Babiga Lemercier, Marc Perez, Charles Univ Technol Troyes Charles Delaunay Inst UMR CNRS 6281 Troyes France ESG Management Sch Paris France

ISBN: (纸本)9781479988259

Social networking services (SNS) have increased in popularity over the last decade. They have become major platforms for e-commerce, personal branding, socialization and information. The success of social networking services like Facebook and Twitter as well as LinkedIn, LiveJournal and Foursquare and the variety of their usages leads their users to create a set of profiles on different SNS. Recently, social networking service aggregators have proposed centralizing the multiple social networking profiles of a given user in order to facilitate his interactions with social networking services. Such aggregators allow the messages received by a profile over multiple SNS to be retrieved, edited and posted with much less effort. Despite their obvious advantages, we highlight in this paper the risk of potential data leaks due to the inexperienced use of such tools. For this purpose, we provide a classification of online SNS and present their specificities with regard to the publicly exposed data of a user. Based on this classification, we investigate the possible insecure use of aggregators with an inappropriate set of SNS, which could lead to rendering sensitive data accessible to people it wasn't intended for. We present a decision tree approach for identifying a possible data leak based on the three following criteria: opinion, interest and location. We finally show the result of this approach on popular social networking aggregators.

关键词： Social networking service social aggregators social network classification social networking based data disclosure decision tree algorithm

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