35 resultados para blended learning methods

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


Relevância:

90.00% 90.00%

Publicador:

Resumo:

On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the behavior of other agents may change as they simultaneously learn how to improve their actions. Non-stationary scenarios can be modeled as Markov Games, which can be solved using the Minimax-Q algorithm a combination of Q-learning (a Reinforcement Learning (RL) algorithm which directly learns an optimal control policy) and the Minimax algorithm. However, finding optimal control policies using any RL algorithm (Q-learning and Minimax-Q included) can be very time consuming. Trying to improve the learning time of Q-learning, we considered the QS-algorithm. in which a single experience can update more than a single action value by using a spreading function. In this paper, we contribute a Minimax-QS algorithm which combines the Minimax-Q algorithm and the QS-algorithm. We conduct a series of empirical evaluation of the algorithm in a simplified simulator of the soccer domain. We show that even using a very simple domain-dependent spreading function, the performance of the learning algorithm can be improved.

Relevância:

90.00% 90.00%

Publicador:

Resumo:

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Relevância:

90.00% 90.00%

Publicador:

Resumo:

The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system along with established techniques of supervised learning leads to the correct classification of sugar samples according to their qualities. In this paper, we offer two new real, public and non-encoded sugar datasets whose attributes were automatically collected using an electronic tongue, with and without pH controlling. Moreover, we compare the performance achieved by several established machine learning methods. Our experiments were diligently designed to ensure statistically sound results and they indicate that k-nearest neighbors method outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further comparison. © 2012 IEEE.

Relevância:

90.00% 90.00%

Publicador:

Resumo:

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Relevância:

90.00% 90.00%

Publicador:

Resumo:

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Relevância:

90.00% 90.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

80.00% 80.00%

Publicador:

Resumo:

As novas demandas sociais e as diretrizes curriculares brasileiras para os cursos de odontologia colocam desafios à prática docente nas instituições de educação superior. Nesse contexto, investigam-se as concepções de qualidade de ensino universitário de professores que atuam como coordenadores de graduação nas faculdades de odontologia do Estado de São Paulo que possuem pós-graduação stricto-sensu, para refletir sobre os desafios da formação docente na área. Como instrumentos de levantamento de dados utilizou-se questionário, contendo perguntas abertas e fechadas e entrevista semi-estruturada, organizada para possibilitar o aprofundamento da discussão. Os dados foram descritos e discutidos mediante análise quantitativa e qualitativa, a partir das três dimensões da prática docente analisadas por Cunha (1995): político-estrutural, curricular e pedagógica. Para este artigo, focalizaram-se apenas os aspectos da dimensão pedagógica, na qual os pontos que expressam posturas mais contraditórias referem-se a métodos de ensino-aprendizagem, participação do aluno e tutoria. Os resultados apontam para concepções de ensino-aprendizagem que oscilam entre modelos tradicionais e inovadores, sinalizando pontos de conflito em relação a paradigmas que se articulam diretamente a questões curriculares e político-estruturais.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Introduction. Bioethics is present in Dentistry and other health areas, as scientific research that results on profession progress, as in proper clinical attendance. The study consists on valuation of teaching-learning methods of Bioethical on Brazilian Dental Schools. Materials and methods. Data collect occurred by semi-structured questioners send by e-mail and correspondence. It was realized descriptive analysis of quantitative answers, and for qualitative answers, it was used content analysis, by categorical analysis technique in according to Bardin. Results. Among 182 Dental Schools actives in Brazil, only 57 (31.3%) showed bioethical discipline in its curricular grid. It was observed the discipline is teaching on theoretical form (77.8%). Principal forms of evaluation are: writing prove (100%) and seminaries (75%). Just 6.4% of professors use bibliographic references about bioethical faced to Odontology specifically. The majority of interviewed person (74.2%) considered that bioethics is related on the direct and indirect form with all others disciplines. In relation to importance of Bioethical on dental surgeon formation, 64.7% emphasized it in professional-patient relation. Conclusion. The Bioethics show teaching and practice method of conserver evaluation, and so, it's necessary others methods directed to reflection of actual problems in odontology area that contribute significantly on integral formation of dental surgeon. © Viguera Editores SL 2009.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Pós-graduação em Educação - FFC

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

80.00% 80.00%

Publicador:

Resumo:

This paper discuss possibilities of use of 3D animation as a tool for teaching Chemistry support. The research proposes to investigate the conception process and development of educational animations to use in a Blended Learning environment in undergraduate chemistry. Associated with general chemistry teachers, were raised the demands and difficulties on the content transmission, and the most relevant topics, about "Atomic Theory" with propose to create appropriate animations to meeting needs of themes. Thinking about offering more dynamic materials, we elaborate animations in a format of "micro-documentary", with a length between 4 and 7 minutes. We use the narration aloud to the subject-matter understanding, leaving the external text as a complement of the animation. The conclusions are positives, students accepted well the format and they proved are able to remember, organize and systematize several information presented in animations. These skills don't ensure knowledge acquisition, but may be considered prerequisites to learning occur.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

This research analyses the positives and/or negatives of external reviews to work's organization developed at the/and by the school. It should be noted that it's a qualitative case of empirical research, and it takes the pattern of case's study, because we held the investigation just in one school, which in turn, belongs to the education's public network by the state, and is located at the São Paulo northwest. The tools employed at this research for the data's collect were the observation, restricted to times of Pedagogical Work Activities Collective from the school, and the semi structured interviews with educational coordinators and the teachers too. We choose educational coordinators and teachers because they are closer with the education and learning methods, as well as their activities have more responsibility in relation to the main function developed by school, that is to teach, in other words, educational processes. This research also concerns an investigation about the educational coordinators and teachers conceptions, in relation to system's implantation external reviews at the schools. The results indicate to incidence of significant interference of the external reviews to/in the organization school's work, as, a teaching practice reorientation from results arising these reviews, or, modifications in the internal rating, since they have followed a tendency towards becoming more similar with their own external reviews. In what concerns the subjects investigated, we can emphasize that mostly submitted alienation with respect to negative effects of the external reviews for school. They showed that are conformed with the reality that they are inserted and in your mostly they proved perceive the positive effects by the implantation of external reviews. We can also add that the data obtained in the research allow us declare that the work of the educational coordinators of this school in presence of external reviews don't...