Recognition of our environment is essentially based on observation, analysis and classification. The elements of our environment are indeed classified by comparison with their similar in modes of hierarchical relational representations. This approach is relatively difficult to formalize, especially when placed in an unsupervised context. That is to say, when it comes to identifying the classes present in a sample from the only information that can be extracted from the objects to be classified. In general, objects are characterized by attributes which it is convenient to represent by points in a multidimensional space. In this context, many classification methods have been developed. Some of them are based on concepts of distances, while others refer to statistical notions where explicit reference is made to the probability density function (pdf) underlying the distribution of data at to classify.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
- Hochschullehrerin für Informatik und Didaktik.-Ausbilderin am Centre Régional des Métiers de l'Éducation et de la Formation.Rabat-Salé-Kenitra. Marokko.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recognition of our environment is essentially based on observation, analysis and classification. The elements of our environment are indeed classified by comparison with their similar in modes of hierarchical relational representations. This approach is relatively difficult to formalize, especially when placed in an unsupervised context. That is to say, when it comes to identifying the classes present in a sample from the only information that can be extracted from the objects to be classified. In general, objects are characterized by attributes which it is convenient to represent by points in a multidimensional space. In this context, many classification methods have been developed. Some of them are based on concepts of distances, while others refer to statistical notions where explicit reference is made to the probability density function (pdf) underlying the distribution of data at to classify. 128 pp. Englisch. Bestandsnummer des Verkäufers 9786204624945
Anzahl: 2 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Bestandsnummer des Verkäufers 26405915654
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand. Bestandsnummer des Verkäufers 407271385
Anzahl: 4 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND. Bestandsnummer des Verkäufers 18405915660
Anzahl: 4 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Eddarouich Souad- Doctor in Artificial Intelligence- Computer science teacher at the Regional Center for Education and Training - CRMEF- Researcher in Machine Learning and Deep- Learning.Recognition of our environment is essentia. Bestandsnummer des Verkäufers 590482188
Anzahl: Mehr als 20 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Recognition of our environment is essentially based on observation, analysis and classification. The elements of our environment are indeed classified by comparison with their similar in modes of hierarchical relational representations. This approach is relatively difficult to formalize, especially when placed in an unsupervised context. That is to say, when it comes to identifying the classes present in a sample from the only information that can be extracted from the objects to be classified. In general, objects are characterized by attributes which it is convenient to represent by points in a multidimensional space. In this context, many classification methods have been developed. Some of them are based on concepts of distances, while others refer to statistical notions where explicit reference is made to the probability density function (pdf) underlying the distribution of data at to classify.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch. Bestandsnummer des Verkäufers 9786204624945
Anzahl: 1 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. ARTIFICIAL INTELLIGENCE AND APPLICATIONS | Edition 1: Neural Networks and Automatic Classification of Multidimensional Data | Souad Eddarouich | Taschenbuch | Englisch | 2022 | Our Knowledge Publishing | EAN 9786204624945 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 121581805
Anzahl: 5 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recognition of our environment is essentially based on observation, analysis and classification. The elements of our environment are indeed classified by comparison with their similar in modes of hierarchical relational representations. This approach is relatively difficult to formalize, especially when placed in an unsupervised context. That is to say, when it comes to identifying the classes present in a sample from the only information that can be extracted from the objects to be classified. In general, objects are characterized by attributes which it is convenient to represent by points in a multidimensional space. In this context, many classification methods have been developed. Some of them are based on concepts of distances, while others refer to statistical notions where explicit reference is made to the probability density function (pdf) underlying the distribution of data at to classify. Bestandsnummer des Verkäufers 9786204624945
Anzahl: 1 verfügbar