| Autor: |
Cazer, Casey L., Al-Mamun, Mohammad A., Kaniyamattam, Karun, Love, William J., Booth, James G., Lanzas, Cristina, Gröhn, Yrjö T. |
| Předmět: |
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| Zdroj: |
Frontiers in Microbiology; 6/30/2020, Vol. 11, p1-3, 3p |
| Abstrakt: |
Keywords: association rule mining; antimicrobial resistance; Escherichia coli; machine learning; multidrug resistance; foodborne bacteria EN association rule mining antimicrobial resistance Escherichia coli machine learning multidrug resistance foodborne bacteria 1 3 3 07/03/20 20200630 NES 200630 In the original article, there was an error in the description and presentation of the false discovery rate. This procedure ranks the rules in each null dataset by a given quality measure and averages the quality measure value across the 100 null datasets at each rank. Association rules were mined from the null datasets, the percentiles of confidence, lift and the absolute value of phi were calculated for each null dataset and averaged across the 100 null datasets. [Extracted from the article] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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