Context: The amount and diversity of data have increased drastically in recent years. However, in certain situations, the data to which a trained Machine Learning model is significantly different from testing data, a problem known as Concept Drift (CD). Because CD can be a serious issue, there has been a wealth of research on how to detect and work around it. However, most of the literature focuses on classification tasks. Objective: Making a Systematic Literature Review (SLR) for CD in the context of regression. Research questions: How to detect CD and how to build CD techniques for regression problems using machine learning? Method: We ran an automatic search process on reference databases, selecting papers from 2010 to August 2020, following the methodological process proposed by (Kitchenhame and Charters) (2007). Results:We selected 41 papers. Drift Detection Methods based on ensembles and neural networks with highlight OS-ELM were the most frequent in the selected papers with superior performance. However, only two papers confirm such superiority statistically. Furthermore, identify CD problems as the batch size, drift points, and where drift happens. Conclusions: SLR focuses on highlighting the existing literature on CD applied to regression.
Abstract. Objective: To propose a teaching model that uses the PBL teaching methodology and AVA resources for high school students. Methods:This is a basic qualitative research. Results:Obtained the proposal of the teaching model, as well as its description and use by both the teacher and the students. Conclusion: Satisfactory results are expected, since the resources used for the proposal have obtained good results in other studies; So that students can improve their communication and leadership.Resumo. Objetivo:Propor um modelo de ensino que utilize a metodologia de ensino PBL e recursos AVAs para alunos do Ensino médio. Métodos: Trata-se de uma pesquisa qualitativa básica. Resultados: Obteve a proposta do modelo de ensino, assim como sua descrição e utilização tanto pelo professor quanto pelos discentes. Conclusão: Espera-se resultados satisfatórios, pois outros estudos apresentaram bons resultados com a adoção de recursos semelhantes; dessa forma os discentes poderão melhorar sua comunicação e espírito de liderança. IntroduçãoO PBL (Problem-Basead Learnig)é considerado uma metodologia de ensino colaborativa e contextualizada, em que através de problemas, exercícios ou projetos propostos pelo professor, e vinculado a aspectos reais, estimulam a aprendizagem dos discentes [Angelo and Bertoni 2012]. A metodologia teve seus primeiros vestígios naárea médica, na escola McMaster, no Canadá; e depois em outras escolas como Harvard e Havaí, nos Estados Unidos a adoram [Pires et al. 2010]. A base do PBLé o problema, visto que todo processo na sala de aula estar relacionado ao mesmo, já que antes de qualquer exposição teórica do conteúdo o professor apresenta o problema ao aluno, para que este tente solucionar, sendo assim os discentes tem que ir em busca de seu conhecimento . No intuito de contribuir com uma melhor participação do aluno no processo de aprendizagem existem os Ambientes Virtuais de aprendizagem (AVAs), esses ambientes têm como características a utilização de recursos digitais (plataformas), com o objetivo de tornar uma dinâmica mais flexível para, por exemplo, a proposta e resolução de exercícios.Seguindo esse pressuposto, o artigo tem por objetivo propor um modelo pedagógico para suporte e utilização da metodologia de ensino do PBL, tendo como auxílio
As demand for computer software continually increases, software scope and complexity become higher than ever. The software industry is in real need of accurate estimates of the project under development. Software development effort estimation is one of the main processes in software project management. However, overestimation and underestimation may cause the software industry loses. This study determines which technique has better effort prediction accuracy and propose combined techniques that could provide better estimates. Eight different ensemble models to estimate effort with Ensemble Models were compared with each other base on the predictive accuracy on the Mean Absolute Residual (MAR) criterion and statistical tests. The results have indicated that the proposed ensemble models, besides delivering high efficiency in contrast to its counterparts, and produces the best responses for software project effort estimation. Therefore, the proposed ensemble models in this study will help the project managers working with development quality software.
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