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Machine learning using multiple logistic regression for antimicrobial and hemolytic peptides prediction and their identification in large proteins
Table 1 - Essential parameters of the models
Parameter | Model | |
Antimicrobial activity prediction | Hemolytic activity prediction | |
Null deviance (null model) | 2961.1 | 865.05 |
df (null model) | 2135 | 623 |
Residual deviance (model with predictors) | 1610.6 | 418.09 |
df (model with predictors) | 2122 | 610 |
χ2 | 1350.5 | 449.96 |
df (number of predictors, i.e. df in the model with predictors – df in the null model) | 13 | 13 |
p-value | << 0.001 | << 0.001 |