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We thus went on to the next step: understanding the data (Step 2).
In mining the data (Step 4), we applied a support vector machine (SVM) to classify the respondents.
The DATA step has two phases, compilation and execution.
The DATA step has executable statements that result in the software taking an action, and declarative statements that provide instructions to read a data set or alter the data's appearance.
It was used only on IBM mainframes and had the main elements of SAS programming, such as the DATA step and the most common procedures in the PROC step.
The DATA step reads in the data and computes the log-weight 'logw' and the interaction term 'rad_atm_int'rad_atm_int
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In the data preparation step (Step 3), we first calculated the mean score of MSLQ.
Rule extraction from the training data (step 3) is the most important and novel step of the whole methodology.
As a new addition, we performed a principal component analysis (PCA) on the recovery data (step 4).
We proposed an iterative refinement scheme that iterates between the depth estimation step and the data fusion step.
A PUFA intake database is created by merging the food consumption data (Step 1) and PUFA concentration data (Step 2).
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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