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  • Andrea Esuli; Alessandro Fabris; Alejandro Moreo; Fabrizio Sebastiani
    978-3-031-20467-8
    2023
    Edition 1
    • Introduces learning to quantify by looking at the supervised learning methods used to perform it
    • Details evaluation measures and protocols to be used for evaluating the quality of the returned predictions
    • Suitable for researchers, data scientists, or PhD students in information retrieval or applied data science
    • This book is open access, which means that you have free and unlimited access

    Open Access

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