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Enhancing dynamic ensemble selection: combining self-generating prototypes and meta-classifier for data classification

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Neural computing and Applications 2024年第32期36卷 20295-20320页

作者： Manastarla, Alberto Silva, Leandro A. Graduate Program in Electrical Engineering and Computing Mackenzie Presbyterian University R. da Consolação 930 - Consolação SP Sao Paulo01302-907 Brazil Computing and Informatics Faculty and Graduate Program in Electrical Engineering and Computing Mackenzie Presbyterian University R. da Consolação 930 - Consolação SP Sao Paulo01302-907 Brazil

In dynamic ensemble selection (DES) techniques, the competence level of each classifier is estimated from a pool of classifiers, and only the most competent ones are selected to classify a specific test sample and predict its class labels. A significant challenge in DES is efficiently estimating classifier competence for accurate prediction, especially when these techniques employ the K-Nearest Neighbors (KNN) algorithm to define the competence region of a test sample based on a validation set (known as the dynamic selection dataset or DSEL). This challenge is exacerbated when the DSEL does not accurately reflect the original data distribution or contains noisy data. Such conditions can reduce the precision of the system, induce unexpected behaviors, and compromise stability. To address these issues, this paper introduces the self-generating prototype ensemble selection (***) framework, which combines meta-learning with prototype selection. The proposed meta-classifier of *** supports multiple classification algorithms and utilizes meta-features from prototypes derived from the original training set, enhancing the selection of the best classifiers for a test sample. The method improves the efficiency of KNN in defining competence regions by generating a reduced and noise-free DSEL set that preserves the original data distribution. Furthermore, the *** framework facilitates tailored optimization for specific classification challenges through the use of hyperparameters that control prototype selection and the meta-classifier operation mode to select the most appropriate classification algorithm for dynamic selection. Empirical evaluations of twenty-four classification problems have demonstrated that *** outperforms state-of-the-art DES methods as well as traditional single-model and ensemble methods in terms of accuracy, confirming its effectiveness across a wide range of classification contexts. © The Author(s), under exclusive licence to Springer-Ver

关键词： Nearest neighbor search

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Multi-criteria rating conversion without relation loss for recommender systems

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International Journal of Computers and Applications 2022年第2期44卷 130-138页

作者： Sitkrongwong, Padipat Maneeroj, Saranya Takasu, Atsuhiro Department of Informatics School of Multidisciplinary Sciences The Graduate University for Advanced Studies SOKENDAI Tokyo Japan Advanced Virtual and Intelligent Computing Center Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand National Institute of Informatics Tokyo Japan

Traditional recommender systems let users provide a single rating indicating their overall preferences toward items. Beside overall rating, multi-criteria recommender systems let users rate on multiple aspects of items with multi-criteria ratings. Most methods in recommender systems are based on collaborative filtering, which makes recommendations by exploiting ratings from neighbor users. However, most of them ignore the fact that rating behaviors of users vary due to their personal preference biases. Thus, exploiting ratings from neighbors directly might result in a poor recommendation. To solve this, the rating conversion techniques have been applied in some single criterion recommendations. For multi-criteria ratings, converting each criterion rating independently might result in loss of relation among criteria ratings. We propose a novel method that simultaneously converts all criteria ratings between users to maintain their implicit relations. The multi-criteria ratings are first normalized by variances of users and principle component analysis is applied to extract user preference patterns. Such patterns are then used for multi-criteria rating conversion. The experiment results show that our method outperforms both current single and multi-criteria rating conversion techniques with RMSEs of 1.1082 and 3.5574 on TripAdvisor and Yahoo datasets respectively, while maintaining considerably high level of prediction coverages. © 2019 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Recommender systems

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Two-level feature selection for naive bayes with kernel density estimation in question classification based on Bloom's cognitive levels

Two-level feature selection for naive bayes with kernel dens...

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2013 5th International Conference on Information Technology and Electrical Engineering, ICITEE 2013

作者： Supriyanto, Catur Yusof, Norazah Nurhadiono, Bowo Sukardi Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia Faculty of Computing Universiti Teknologi Malaysia Skudai Malaysia Program of Informatics Engineering College of Computing and Informatics Adhi Guna Palu Indonesia

ISBN: (纸本)9781479904259

This paper proposes a two-level feature selection to improves Naïve Bayes with kernel density estimation. The performance of the proposed feature selection is evaluated on question item set based on Bloom's cognitive levels. This two-level feature selection contains of filter and wrapper based feature selection. This paper uses chi square and information gain as the filter based feature selection and forward feature selection and backward feature elimination as the wrapper based feature selection. The result shows that the two-level feature selection improves the Naïve Bayes with kernel density estimation. The combination of chi square and backward feature elimination give more optimal quality than the other combination. © 2013 IEEE.

关键词： Feature Selection

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Determining environmental indicators related to the propagation of contagious diseases and health issues: A Systematic Literature Review 18

Determining environmental indicators related to the propagat...

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18th Iberian Conference on Information Systems and Technologies, CISTI 2023

作者： Portillo, Janeth Dominguez Peralta, Laura M. Rodriguez Sampaio, Paulo N. M. Nunes, Eldman De Oliveira Faculty of Information Technologies and Data Science Mexico Graduate Program in Computing and Systems Bahia Salvador Brazil

ISBN: (纸本)9789893347928

The environmental indicators provide significant information in order to describe the state of a phenomenon, environment or area [1]. This paper addresses the indicators present in the air and their relationship in the accommodation and transmission of viruses, as well as how these environmental indicators can lead to health problems. Therefore, the main goal of this work is to review the scientific contributions in the literature in order to determine and select the potential environmental indicators present in indoor environments which have an impact on the health of people who work and live within these spaces. For this purpose, we carried out a Systematic Literature Review (SLR) related to environmental monitoring, COVID-19, Internet of things, air pollution and environmental indicators within indoor spaces. This SLR allowed us to identify indicators that according to their level of presence can represent a high risk for people's health. Therefore, the process of planning, conducting and reporting the Systematic Literature Review enabled us not only to identify some environmental indicators, but also their corresponding monitoring advantages and disadvantages, and multiple perspectives and approaches of each contribution in the literature. Further on, this study will be the basis for the proposal of an automatic and intelligent platform based on Internet of Things for monitoring indoor environments in order to detect high risk levels for the contamination of contagious diseases. © 2023 ITMA.

关键词： COVID-19

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Sports Analytics: A Comparison of Machine Learning Perfomance for Profiling Badminton Athlete 1

Sports Analytics: A Comparison of Machine Learning Perfomanc...

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1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022

作者： Sinadia, Herbie Ewaldo Murwantara, I Made Universitas Pelita Harapan Faculty Of Computer Science Graduate Program Informatics Dept. Tangerang Banten Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Sports analytics have become an important part in the improvement of athlete performances in the last decade. Badminton is one such sport where sports analytics can prove beneficial for its athletes. By incorporating data analysis and machine learning techniques, we can learn more about an athlete's performance and profile them via their results in official badminton matches, and coaches as well as athletes may use the results to identify possible improvements for the athlete. This work presents a model to profile the performances of two Indonesian badminton athletes through machine learning using official score data of matches played from 2018 to 2021. We have built a model that performs athlete profiling through regression, classification, and clustering methods. Our result shows that Random Forest outperformed SVM method on regression and the two methods performed similarly on classification, while K-means and hierarchical clustering models displayed similar results in data clustering. © 2022 IEEE.

关键词： Sports

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Evaluation of an agent-based reinforcement learning framework for model-based testing 7

Evaluation of an agent-based reinforcement learning framewor...

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7th International Congress on Ambient Intelligence, Software Engineering, and e-Health and Mobile Health, AmITIC 2024

作者： Ramírez-Méndez, Jose Quesada-López, Christian University of Costa Rica Graduate Program in Computing and Informatics San Pedro Costa Rica University of Costa Rica Department of Computer Science and Informatics San Pedro Costa Rica

ISBN: (纸本)9798350364538

This study evaluates an agent-based reinforcement learning framework for model-based testing (MBT). The framework's performance was assessed on three key metrics: effectiveness and efficiency in achieving model coverage objectives, the quantity and uniqueness of generated test cases, and code coverage. The results show improved metrics for the framework compared to traditional testers in model coverage evaluation and test case metrics. Specifically, the framework achieved higher effectiveness and efficiency, generating a higher average number of test cases with a substantial proportion of unique cases, indicating more diverse and thorough testing. Additionally, the framework, along with random and greedy testers, achieved over 70% coverage across branch, method, and line code metrics. The framework showed slightly higher values in method and line coverage compared to other testers. The evaluation highlights the use of agent-based reinforcement learning to support model-based testing in planning test case generation, exploring models using multiple strategies, and learning guided by testing metrics. Future work will focus on further refining the framework learning model, including error coverage evaluation, and testing its applicability across different software systems. © 2024 IEEE.

关键词： Adversarial machine learning

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Implementing a multi-user tour guide system with an embodied conversational agent

Implementing a multi-user tour guide system with an embodied...

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5th International Conference on Active Media Technology, AMT 2009

作者： Čereković, Aleksandra Huang, Hsuan-Hung Furukawa, Takuya Yamaoka, Yuji Pandžić, Igor S. Nishida, Toyoaki Nakano, Yukiko Faculty of Electrical Engineering and Computing Zagreb Croatia Graduate School Informatics Kyoto University Japan Dept. of Computer and Information Science Faculty of Science and Technology Seikei University Tokyo Japan

ISBN: (纸本)9783642048746

In recent years, computer-generated interactive virtual characters, called Embodied Conversational Agents (ECAs), are subjects of considerable ongoing research. Nevertheless, their conversational abilities are mediocre compared to real human behaviors. Among limitations, most of ECAs are incapable of participating in natural conversations in which the number of participants can change dynamically. In the ongoing work we investigate principles of integrating a multi-user support in an ECA system. We present experiments and implementation approach of a prototype system in which a tour guide ECA interacts with one or two users. The system combines different technologies to detect and address the system users and draw their attention. Experimental interaction with the system produces encouraging results. The system can address the user's appearance, departure, decreased level of interest and identify his conversational role. © 2009 Springer-Verlag.

关键词： Behavioral research

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Toward a multi-culture adaptive virtual tour guide agent with a modular approach

Toward a multi-culture adaptive virtual tour guide agent wit...

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作者： Huang, Hung-Hsuan Cerekovic, Aleksandra Pandzic, Igor S. Nakano, Yukiko Nishida, Toyoaki Graduate School of Informatics Kyoto University Kyoto Japan Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Faculty of Science and Technology Seikei University Seikei Japan

Embodied conversational agents (ECAs) are computer-generated, human-like characters that interact with human users in face-to-face conversations. ECA is a powerful tool for representing cultural differences and is suitable for interactive training or edutainment systems. This article presents preliminary results from the development of a culture-adaptive virtual tour guide agent for serving Japanese, Croatian, and general Western users by displaying appropriate verbal and non-verbal behaviors. It is being implemented in Generic ECA Framework, a modular framework for developing ECAs. Dividing the ECA functions into reusable and loosely coupled modules minimizes the effort required to implement additional behavior and facilitates incremental scale up of the system. © Springer-Verlag London Limited 2009.

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Lung cancer diseases diagnostic asistance using Gray color analysis

Lung cancer diseases diagnostic asistance using Gray color a...

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International Conference on Computational Intelligence, Modelling and Simulation

作者： Paulus Gaol, Ford Lumban Graduate Program in Informatics Engineering Department of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9780769542621

Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to read cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radiologic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results. © 2010 IEEE.

关键词： Diseases

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Semantic interoperability in tools for intercultural collaboration

Semantic interoperability in tools for intercultural collabo...

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3rd International Conference on Active Media Technology

作者： Funakoshi, K Sugiyama, K Ishida, T Yoshino, T Munemori, J Zhang, HJ So, ZZ NTT Communication Science Laboratories NTT Corporation Japan Graduate School of Informatics Kyoto University Japan Faculty of Systems Engineering Wakayama University Japan Institute of Computing Technology Chinese Academy of Science China

ISBN: (纸本)0780390350

In software/content development in intercultural environments, collaboration among participants and effective administration are crucial for overall successful projects. Various tools are used to achieve the collaboration and the administration of the project: no single groupware is sufficient for both collaboration support and management. Therefore, interoperability among various tools employed in one project is essential for efficient collaboration. To establish semantic interoperability of collaboration tools, we have designed an RDF tag set that can function as vocabulary to describe information interoperably among the tools. In this paper, we propose a tag set to describe information in intercultural projects and show how the data in collaboration tools and project management tools are integrated with those semantic tags. With the tag set and the supporting method, it is expected that the members and the administrators do not have to pay much efforts to keep the collaboration status.

关键词： Semantics

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