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Exact(50)
One model was used to assess the impact of the level of S/P-ratios at a specific time relative to the outcome risk (LEVEL model) and one was used to assess the impact of increases in S/P-ratios in a specific interval relative to the outcome risk (INCREASE model).
Data smoothing did not increase model fit precision.
Thus, target descriptors would not contribute to increase model performance.
The BRT models were simplified by dropping variables that did not increase model performance.
This analysis also confirmed the relevance of a linear leaf area (LA) increase model.
The incorporation into the model of such factors is very likely to increase model robustness.
Similar(10)
For predictive purposes, PLS1 models were constructed for individual Y variables to increase model-specificity and reliability.
A direct benefit is the potential for increased model reuse.
Furthermore, these limitations scale prohibitively with increasing model size.
However, increasing model complexity will negatively influence the traceability and comprehension of the existing model.
Adding more predictor variables have proven to be helpful in increasing model accuracy.
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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