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Multiple variables were tested and their impact on productivity metrics examined.
Single and multiple variables were used to develop empirical models to predict PM2.5 concentrations for each of the five significant scales of the corresponding seasons (Table 3).
Through PCA the original multiple variables were represented by seven principal components (PCs) and, hence, led to more than 99% reduction of input parameters in the ANN model.
We selected regression because we wanted to determine if the relationships changed when multiple variables were considered, and a stepwise regression allowed us to examine relationships to evolution acceptance based on individual and combined variables.
Multiple variables were included in the model, including all variables with significant interactions.
To create a prediction model, logistic models with single or multiple variables were used to calculate the cardiac mortality.
Similar(45)
The optimal properties of information-theoretic terms in assessing variability and correlation between multiple variables are familiar to the machine learning and statistics communities but perhaps not well known in fields of epidemiology and medical statistics.
Statistical evaluation of multiple variables was performed.
The credible intervals are increased as multiple variables are combined.
Making sense of big data sets with multiple variables is a classic challenge for the field of machine learning.
Optimizing for multiple variables is notoriously challenging; even when leaders unambiguously express their commitment to social and environmental goals by, for example, modifying their corporate mission statements, they face major tradeoffs.
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