Bayesian networks in educational assessment / Russell G. Almond ... [et al.] |
Pubbl/distr/stampa | New York, : Springer, 2015 |
Descrizione fisica | XXXIII, 662 p. : ill. ; 24 cm |
Soggetto topico |
62B10 - Statistical aspects of information-theoretic topics [MSC 2020]
62F15 - Bayesian inference [MSC 2020] 94A15 - Information theory (general) [MSC 2020] 94Cxx - Circuits, networks [MSC 2020] |
Soggetto non controllato |
Artificial Intelligence
Bayes net Bayesian model education ECD Evidence-Centered Design Evidence-centered assessment design Uncertainty |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0113099 |
New York, : Springer, 2015 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
|
Bayesian networks in educational assessment / Russell G. Almond ... [et al.] |
Pubbl/distr/stampa | New York, : Springer, 2015 |
Descrizione fisica | XXXIII, 662 p. : ill. ; 24 cm |
Soggetto topico |
62B10 - Statistical aspects of information-theoretic topics [MSC 2020]
62F15 - Bayesian inference [MSC 2020] 94A15 - Information theory (general) [MSC 2020] 94Cxx - Circuits, networks [MSC 2020] |
Soggetto non controllato |
Artificial Intelligence
Bayes net Bayesian model education ECD Evidence-Centered Design Evidence-centered assessment design Uncertainty |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN00113099 |
New York, : Springer, 2015 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing / Hyung-Sup Jung, Saro Lee |
Autore | Jung Hyung-Sup |
Pubbl/distr/stampa | Basel, Switzerland : , : MDPI, , 2019 |
Descrizione fisica | 1 electronic resource (438 p.) |
Soggetto non controllato |
artificial neural network
model switching sensitivity analysis neural networks logit boost Qaidam Basin land subsidence land use/land cover (LULC) naïve Bayes multilayer perceptron convolutional neural networks single-class data descriptors logistic regression feature selection mapping particulate matter 10 (PM10) Bayes net gray-level co-occurrence matrix multi-scale Logistic Model Trees classification Panax notoginseng large scene coarse particle grayscale aerial image Gaofen-2 environmental variables variable selection spatial predictive models weights of evidence landslide prediction random forest boosted regression tree convolutional network Vietnam model validation colorization data mining techniques spatial predictions SCAI unmanned aerial vehicle high-resolution texture spatial sparse recovery landslide susceptibility map machine learning reproducible research constrained spatial smoothing support vector machine random forest regression model assessment information gain ALS point cloud bagging ensemble one-class classifiers leaf area index (LAI) landslide susceptibility landsat image ionospheric delay constraints spatial spline regression remote sensing image segmentation panchromatic Sentinel-2 remote sensing optical remote sensing materia medica resource GIS precise weighting change detection TRMM traffic CO crop training sample size convergence time object detection gully erosion deep learning classification-based learning transfer learning landslide traffic CO prediction hybrid model winter wheat spatial distribution logistic alternating direction method of multipliers hybrid structure convolutional neural networks geoherb predictive accuracy real-time precise point positioning spectral bands |
ISBN |
9783039212163
3039212168 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910367564103321 |
Jung Hyung-Sup
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Basel, Switzerland : , : MDPI, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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