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Machine learning classifiers &Classifier ensample

Language EnglishEnglish
Book Paperback
Book Machine learning classifiers &Classifier ensample Rania Ibrahim
Libristo code: 44618565
Publishers LAP LAMBERT Academic Publishing, November 2023
There are an emergent machine learning(ML) algorithms to classify land-cover and land-use. In this b... Full description
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There are an emergent machine learning(ML) algorithms to classify land-cover and land-use. In this book we focus on the relatively mature methods (seven methods) support vector (SVM) machines, decision trees (DTs), artificial neural networks, k-nearest neighbours (k-NN), naïve Bayes, Boosting and Random forest (RF).Accurate and timely collection of urban land use and land cover information is crucial for many aspects of urban development and environment protection.Accurate land covers classification is challenging. Improving land cover classification is a hot topic. It is needed for many applications such as land use land cover mapping environmental monitoring, natural resource management, urban planning, and management and change detection. Then a number of ensample methods were studied to combine various classifiers.

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About the book

Full name Machine learning classifiers &Classifier ensample
Language English
Binding Book - Paperback
Date of issue 2023
Number of pages 52
EAN 9786206845867
ISBN 6206845869
Libristo code 44618565
Weight 96
Dimensions 150 x 220 x 4
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