Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science

Cover -- Copyright -- Title Page -- Contents -- Preface -- Acknowledgments -- Introduction -- Empirical Methods in Machine Learning -- Scope and Outline of this Book -- Intended Readership -- Validity -- Validity Problems in NLP and Data Science -- Bias Features -- Illegitimate Features -- Circular...

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Bibliographic Details
Main Author: Riezler, Stefan (Author)
Other Authors: Hagmann, Michael (Contributor)
Format: Book/Monograph
Language:English
Published: San Rafael Morgan & Claypool Publishers [2022]
Series:Synthesis lectures on human language technologies #55
In: Synthesis lectures on human language technologies (#55)

Online Access:Aggregator, lizenzpflichtig: https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6823453
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Validity, reliability, and significance: empirical methods for NLP and data science by Riezler, Stefan (Author) , Hagmann, Michael (Author) ,

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Validity, reliability, and significance: empirical methods for NLP and data science by Riezler, Stefan (Author) , Hagmann, Michael (Author) ,

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Validity, reliability, and significance: empirical methods for NLP and data science by Riezler, Stefan (Author) , Hagmann, Michael (Author) ,


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