Ai Feedback
Exact(7)
Both methods were expected to provide optimal solution characteristic by the full accuracy about all three axes, which was confirmed.
On the other hand, it was also demonstrated that online learning schemes together with random sampling or data sketching methods were expected to play instrumental roles in solving large-scale optimization tasks.
The two methods were expected to return similar, though not identical, results.
Consequently, even if probabilities of drop-out differed, both methods were expected to be unbiased.
The limits of agreement were calculated as bias ± two SD, and defined the range in which 95% of the differences between the methods were expected to lie.
These methods were expected to improve all of the original items to a greater or lesser extent, and to improve the modified scales whenever a new item with higher IRT scores replaced a Legacy item.
Similar(53)
These methods are expected to result in improved driving stability.
Some simple methods are expected to help the selection.
Empirical methods are expected to be more reliable when the structure under investigation is relatively rigid.
Iterative methods are expected to be time-consuming due to the large parameter space.
All rationally engineered methods are expected to perform significantly above 0.5 in terms of AUC.
Related(16)
procedures were expected
methods were projected
methods were forecasted
methods were perceived
means were expected
modes were expected
methods were preferred
methods were suggested
methods were employed
methods were outdated
methods were used
methods were developed
methods were tried
methods demonstrated expected
methods were deemed
methods were proposed
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