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In this paper, principles, components, and functions of the GBTB are developed.
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Model run with principle components has also provided satisfying performance.
When plotting the first two principle components, dogs and wolves were separated as two distinct groups (Fig. 2c).
Principle Components and Factor Analysis.
(1) Principle Components and Factor Analysis First, varimax rotation was used for principle components analysis.
PCA is used to identify the principle components (PCs).
First, varimax rotation was used for principle components analysis.
These new set of variables are known as principle components.
As a final quality control step we performed a principle component analysis and plotted the first two principle components to show that replicated samples were grouping together.
Resampling the data using a principle component analysis (PCA): We used PCA to calculate the principle components (or eigen-vectors) of the spectrograms of each fish species.
Briefly, PCA transforms possibly correlated variables into a smaller number of uncorrelated variables called principle components.
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