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Machine learning using multiple logistic regression for antimicrobial and hemolytic peptides prediction and their identification in large proteins
Table 1 - Sizes of sets used in ML for antimicrobial activity prediction
Set | Split | Number of peptides |
AMP (1335) | Training set: 80% | 1068 |
Test set: 20% | 267 | |
Non-AMP (1335) | Training set: 80% | 1068 |
Test set: 20% | 267 | |
| Training set: 80% (2136) Test set: 20% (534) | Sum: 2670 |