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Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
| Advances in Artificial Intelligence: Models, Optimization, and Machine Learning |
| Autore | Leon Florin |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (362 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
large margin nearest neighbor regression
distance metrics prototypes evolutionary algorithm approximate differential optimization multiple point hill climbing adaptive sampling free radical polymerization autonomous driving object tracking trajectory prediction deep neural networks stochastic methods applied machine learning classification and regression data mining ensemble model engineering informatics gender-based violence in Mexico twitter messages class imbalance k-nearest neighbor instance-based learning graph neural network deep learning hyperparameters machine learning optimization inference metaheuristics animal-inspired exploration exploitation hot rolled strip steel surface defects defect classification knockout tournament dynamic programming algorithm computational complexity combinatorics intelligent transport systems traffic control spatial-temporal variable speed limit multi-agent systems reinforcement learning distributed W-learning urban motorways multi-agent framework NET framework simulations agent-based systems agent algorithms software design multisensory fingerprint interoperability DeepFKTNet classification generative adversarial networks image classification transfer learning plastic bottle |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advances in Artificial Intelligence |
| Record Nr. | UNINA-9910580212403321 |
Leon Florin
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical Data Modeling and Machine Learning with Applications
| Statistical Data Modeling and Machine Learning with Applications |
| Autore | Gocheva-Ilieva Snezhana |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (184 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
mathematical competency
assessment machine learning classification and regression tree CART ensembles and bagging ensemble model multivariate adaptive regression splines cross-validation dam inflow prediction long short-term memory wavelet transform input predictor selection hyper-parameter optimization brain-computer interface EEG motor imagery CNN-LSTM architectures real-time motion imagery recognition artificial neural networks banking hedonic prices housing quantile regression data quality citizen science consensus models clustering Gower's interpolation formula Gower's metric mixed data multidimensional scaling classification data-adaptive kernel functions image data multi-category classifier predictive models support vector machine stochastic gradient descent damped Newton convexity METABRIC dataset breast cancer subtyping deep forest multi-omics data categorical data similarity feature selection kernel density estimation non-linear optimization kernel clustering |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557359003321 |
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Gocheva-Ilieva Snezhana
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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