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There are eight samples for each person.
Instead, it manages a set of samples for each pixel.
Based on averages of 30 min. samples for each period.
Diversity can be introduced into the ensemble by creating different training samples for each model.
This experiment was divided into four groups with 10 block samples for each group.
This resulted in 18 samples for each single taste aroma combination.
In addition, perpendicular and parallel test samples for each group were set up for bending tests.
In this case, training dataset has 1200 samples (200 samples for each working state), while testing dataset has 600 samples (100 samples for each working state).
The six samples were made up of three samples for each of the two seasons.
The data presented in this paper represent analysis of three representative samples for each sample type.
Data were expressed relative to one of the three MC7-L1 samples for each gene.
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CEO of Professional Science Editing for Scientists @ prosciediting.com