Your English writing platform
Discover LudwigExact(52)
Our predictors were post-traumatic headache presence, intensity, and frequency.
Each of our predictors were chosen because of their relation to visual search.
The value of Pseudo R2 is 0.4608 shows that our predictors account for 46.08% of change in our outcome.
Compared to acceptance of evolution, our measure of evolutionary familiarity showed fewer significant differences with regard to our predictors.
From these data we conclude that our predictors of low prevalence performance are uniquely suited to account for low prevalence search performance, not visual search in general.
In terms of the theoretical, the pattern of relationships between our predictors and both accuracy and target-absent reaction time suggest that our predictors might be associated with an individual's low prevalence quitting threshold, hinting at a potential mechanism for the relationships.
Similar(8)
b Difference between our predictor and other two methods.
We carried out a hold-out validation of our predictor.
Our predictor generated 1,107,876 drug-target combinations with associated leave-one-out scores.
Before we conducted our main analysis we undertook an examination of our predictor variables in respect to potential interactions between our predictor variables when modeling the probability of completion.
We train our predictor using the statistical model of PU because we are doing analysis on the offline data.
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