Your English writing platform
Discover LudwigExact(59)
Based on AME and MAE, the seasonal and global models had the smallest error in their modeling performance.
But it turns out the models had the right idea.
Thus, both models had the same number of parameters.
It is not the case that neither of the 6S models had the feature.
The models fitted with random-parameters negative binomial models had the best performance in the process.
These three models had the highest sensitivity and specificity for predicting 6-y lung cancer incidence in the PLCO chest radiography arm, with sensitivities >79.8% and specificities >62.3%.
The PLCOm2012, Bach, and Two-Stage Clonal Expansion incidence models had the best overall performance, with AUCs >0.68 in the NLST and >0.77 in the PLCO.
Results showed the HPLN-ML models had the best goodness-of-fit and efficiency, and models with ML priors yielded estimates with the lowest standard errors.
Optimized models had the root mean-squared errors of 26.1 nm/min and 0.103 nm for the etch rate and surface roughness, respectively.
A few of the models had the good grace to look embarrassed; most seemed to think it was a bit of a laugh.
Similar(1)
Thus RDF models have the form of a directed graph.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com