Search results for "Active Learning"

showing 10 items of 184 documents

Active learning strategies for the deduplication of electronic patient data using classification trees.

2012

Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…

Active learningComputer scienceActive learning (machine learning)Information Storage and RetrievalContext (language use)Health InformaticsSemi-supervised learningMachine learningcomputer.software_genreSet (abstract data type)Artificial IntelligenceBaggingData deduplicationElectronic Health RecordsHumansbusiness.industryString (computer science)Decision TreesOnline machine learningComputer Science ApplicationsData miningArtificial intelligenceMedical Record LinkageString metricbusinesscomputerAlgorithmsJournal of biomedical informatics
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Active Learning for Monitoring Network Optimization

2012

Kernel-based active learning strategies were studied for the optimization of environmental monitoring networks. This chapter introduces the basic machine learning algorithms originated in the statistical learning theory of Vapnik (1998). Active learning is closer to an optimization done using sequential Gaussian simulations. The chapter presents the general ideas of statistical learning from data. It derives the basics of kernel-based support vector algorithms. The active learning framework is presented and machine learning extensions for active learning are described in the chapter. Kernel-based active learning strategies are tested on real case studies. The chapter explores the use of a c…

Active learningComputer scienceActive learning (machine learning)Kernel-based support vector algorithmsMachine learningGaussian simulationsData scienceMonitoring network optimization
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Remote sensing image segmentation by active queries

2012

Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…

Active learningComputer scienceActive learning (machine learning)SvmMultispectral image0211 other engineering and technologies02 engineering and technologyMultispectral imageryClusteringMultispectral pattern recognitionArtificial Intelligence0202 electrical engineering electronic engineering information engineeringSegmentationCluster analysis021101 geological & geomatics engineeringRetrievalPixelbusiness.industryLinkageHyperspectral imagingPattern recognitionRemote sensingSupport vector machineMultiscale image segmentationHyperspectral imageryPixel ClassificationSignal Processing020201 artificial intelligence & image processingHyperspectral Data ClassificationComputer Vision and Pattern RecognitionArtificial intelligencebusinessAlgorithmsSoftwareModel
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Discovering single classes in remote sensing images with active learning

2012

When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…

Active learningComputer scienceActive learning (machine learning)business.industryPattern recognitionSemi-supervised learningRemote sensingMachine learningcomputer.software_genreSupport vector machineActive learningLife ScienceSupport Vector Data DescriptionArtificial intelligencebusinessClassifier (UML)computerChange detection2012 IEEE International Geoscience and Remote Sensing Symposium
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Improving active learning methods using spatial information

2011

Active learning process represents an interesting solution to the problem of training sample collection for the classification of remote sensing images. In this work, we propose a criterion based on the spatial information that can be used in combination with a spectral criterion in order to improve the selection of training samples. Experimental results obtained on a very high resolution image show the effectiveness of regularization in spatial domain and open challenging perspectives for terrain campaigns planning. © 2011 IEEE.

Active learningContextual image classificationComputer sciencebusiness.industryvery-high-resolution (VHR) imagesTerrainspatial informationsupport vector machines (SVMs)Machine learningcomputer.software_genreRegularization (mathematics)Support vector machineArtificial intelligencebusinessImage resolutioncomputerSpatial analysis
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Strategies for Active Learning to Improve Student Learning and Attitudes Towards Physics

2021

Over the last several years, active learning methods and strategies have received considerable attention from the educational community and are commonly presented in the related literature as a credible solution to the reported lack of efficacy of more “traditional” educative approaches. Research has shown that a possible factor is the strongly contextualized nature of active learning that focuses on the interdependence of situation and cognition. In this paper, we report the results of a Symposium with different contributions in the field of research on active learning. We start with a system analysis of the mental processes involved in learning physics which explains how active learning i…

Active learningISLE frameworkPre-service science teacher inquirySettore FIS/08 - Didattica E Storia Della FisicaActive engagementContext (language use)CognitionSystem analysis of mental processesField (computer science)Teacher preparationPhysics theatre in learningActive learningMathematics educationLack of efficacyStudent learning
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Active Learning Methods and Strategies to Improve Student Conceptual Understanding: Some Considerations from Physics Education Research

2020

Active learning methods and strategies are credited to be an important means for the development of student cognitive skills. This paper describes some forms of active learning common in Physics Education and briefly introduces some of the pedagogical and psychological theories on the basis of active learning. Then, some evidence for active learning effectiveness in developing students’ critical cognitive skills and improving their conceptual understanding are examined. An example study regarding the effectiveness of an Inquiry-based learning approach in helping students to build mechanisms of functioning and explicative models, and to identify common aspects in apparently different phenome…

Active learningSettore FIS/08 - Didattica E Storia Della FisicaPhysics educationActive learningComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationCognitive skillPsychology
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Educating to inspire active learning approaches in mathematics in Norwegian universities

2021

This is a report of an analysis of some of the data generated by a national survey of teaching approaches used in higher education mathematics courses. The overall purpose of the survey was to explore how widespread is the use of teaching approaches that might promote students’ active learning of mathematics. The paper includes a brief presentation of the authors meaning of the expression “teaching actions that have the potential to promote active learning”. The analysis focuses on the responses of 95 lecturers working in 13 Norwegian HE institutions. The goal is to expose underlying patterns in lecturers’ responses to questions about the teaching actions they may incorporate in their pract…

Active learninglanguageMathematics educationComputingMilieux_COMPUTERSANDEDUCATIONNorwegianVDP::Mathematics and natural science: 400::Mathematics: 410language.human_language
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The Study of the Scale through Space. Teaching Innovation Experience among Architecture Schools: Malaga, Seville and Palermo

2018

The educational innovation project object of this communication focuses on the scale problems that arise in the projects of territorial planning carried out in architecture schools, but also in the loss of the scale concept related to thought and drawing. The project involved collaboration among the Schools of Architecture of Malaga, Palermo and Seville with the aim of carrying out a practical exercise among the students of two subjects that, working on different scales, addressed similar concepts. In particular, following an PBL methodology based on collaborative projects, the planning of the N-340 road in the city of Nerja (Málaga) was carried out. Firstly, the territorial scale is addres…

Active learningproblem-based learning (PBL)business.industryTeaching methodlcsh:Aeducational innovation projectlandscapeSpace (commercial competition)Landscape designterritorial planningcollaborative project-based learningactive learningScale (social sciences)teaching methodsActive learningtourismMathematics educationSociologylcsh:General WorksArchitectureurbanismbusinessUrbanismTourismThe 2nd Innovative and Creative Education and Teaching International Conference
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Continued Multidisciplinary Project-based Learning – Implementation in Health Informatics

2008

Summary Objectives: Problem- and project-based learning are approved methods to train students, graduates and post-graduates in scientific and other professional skills. The students are trained on realistic scenarios in a broader context. For students specializing in health informatics we introduced continued multidisciplinary project-based learning (CM-PBL) at a department of medical informatics. The training approach addresses both students of medicine and students of computer science. Methods: The students are full members of an ongoing research project and develop a project-related application or module, or explore or evaluate a sub-project. Two teachers guide and review the students’ …

Advanced and Specialized NursingInternetMedical educationComputer sciencebusiness.industryHealth InformaticsContext (language use)Problem-Based LearningAlternative educationProject-based learningHealth informaticsFormative assessmentHealth Information ManagementProblem-based learningMultidisciplinary approachActive learningHospital Information SystemsComputingMilieux_COMPUTERSANDEDUCATIONInterdisciplinary CommunicationProgram DevelopmentbusinessMedical InformaticsMethods of Information in Medicine
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