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Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science - Synthesis Lectures on Human Language Technologies Stefan Riezler
Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science - Synthesis Lectures on Human Language Technologies
Stefan Riezler
Addresses methodological questions that include the problems of validity, reliability, and significance. In the case of machine learning, these correspond to whether a model predicts what it purports to predict, whether its performance is consistent across replications, and whether a performance difference between two models is due to chance.
165 pages
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2021年12月30日 |
| ISBN13 | 9781636392714 |
| 出版社 | Morgan & Claypool Publishers |
| ページ数 | 165 |
| 寸法 | 150 × 220 × 10 mm · 294 g |
| 言語 | 英語 |