Lingua: Inglese
Editore: LAP Lambert Academic Publishing, 2024
ISBN 10: 6208116228 ISBN 13: 9786208116224
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2024
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Comparing Supervised & Unsupervised ML for Fake News Detection | Sufanpreet Kaur (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786208116224 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208116228 ISBN 13: 9786208116224
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208116228 ISBN 13: 9786208116224
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Sep 2024, 2024
ISBN 10: 6208116228 ISBN 13: 9786208116224
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 64 pp. Englisch.
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Editore: LAP LAMBERT Academic Publishing Sep 2024, 2024
ISBN 10: 6208116228 ISBN 13: 9786208116224
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Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6208116228 ISBN 13: 9786208116224
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This investigation aims to develop a robust framework for detecting false information by comparing supervised and unsupervised machine learning algorithms. Unsupervised algorithms identify patterns without pre-labeled data, while supervised algorithms use labeled datasets to guide detection. The evaluation focuses on accuracy, precision, recall, and F1 score to assess each algorithm's effectiveness. The study details dataset composition, preprocessing techniques, and the strengths and limitations of each method. It utilizes Kaggle's dataset, featuring various news stories classified through meticulous verification, including real, fraudulent, and mixed authenticity levels. This research emphasizes the importance of precise labeling and preprocessing, aiming to enhance the development of effective fake news detection systems using advanced machine learning and natural language processing techniques.