Your English writing platform
Discover LudwigExact(60)
The data was randomly divided to the training, prediction and validation sets.
The total group was randomly divided into one intervention group and one control group.
The complete data was randomly divided into a training and validation dataset.
First, the Kt:p-target dataset was randomly divided into 10 folds.
It was randomly divided into training data (70 %) and testing data (30%%).
Each set of training molecules was randomly divided into 10 equally sized sets or folds.
The sample was randomly divided into five groups of 15 teeth each.
The experimental area was randomly divided into three control transects and three trawling transects each ∼1.5 km long.
The whole dataset was randomly divided into a 70% training (n = 210) and 30% test set (n = 90).
The data was randomly divided into a training set and a test set in the ratio of 8 2.
To that end, the data set was randomly divided into calibration (40%) and validation (60%) subsamples (using IBM SPSS 23).
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