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Titlebook: Advanced Machine Learning Technologies and Applications; First International Aboul Ella Hassanien,Abdel-Badeeh M. Salem,Tai-hoo Conference

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Lecture Notes in Computer Scienceunt of pairs of objects belonging to different decision classes that are not discerned by discretized attributes, averaged over all possible choices of binary discretization cuts over the attribute ranges. We prove that such a function can be rewritten by means of distances between the original nume
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Suzanne Bakken,Theresa A. Koleckarch Institute, Nagpur, India). Geometrical and Textural features were calculated for segmented region. Once the features were computed for each region of interest (ROI), they are used as inputs to Artificial Neural Network (ANN) for classification as Benign or Malignant. Results of Rough k-means se
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https://doi.org/10.1007/978-3-030-06109-8fic value made the proposed algorithm flexible and robust against different image characteristics. The effectiveness of the proposed method for a variety of images including different objects of metals and dielectrics are examined in experiments.
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Rough Sets-Based Machine Learning over Non-deterministic Data: A Brief Surveyb und zwischen den Prozessen. Das HaLiMo fokussiert so die operative Auftragsabwicklung mit den wesentlichen Informations- und Materialflüssen und zeigt Beziehungen und Wechselwirkungen zwischen den einzelnen Elementen der unternehmensinternen Lieferkette auf.
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Learning a Table from a Table with Non-deterministic Information: A Perspective978-3-322-87920-2
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Parameterised Fuzzy Petri Nets for Approximate Reasoning in Decision Support Systems978-3-662-43542-7
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New Method for Finding Rules in Incomplete and Distributed Information Systems Controlled by Reducts978-3-662-12804-6
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