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It was found that PCA and PCG each have their own benefits and disadvantages.
The results showed that PCA provided clear visualization identifying different types of adulterants over the score plots.
Regardless, we reiterate that PCA does not isolate distinct clusters it only enables reviewing data from possibly more useful perspectives.
It is evident that PCA can be used as one of the predominant techniques to assess groundwater quality.
The results show that PCA has a very small effect on the overall performance while LDA provides a considerable improvement.
The obtained results demonstrate that PCA and SVMs could classified urine samples into three classes according to low, medium and high creatinine levels (CLs).
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From Table 1, it can be seen that PCA-Gabor captures the most amount of signal variance with PCA coming in second.
These results shown that PCA-CVANN and FCM-CVANN classified Doppler signals successfully.
It can been observed that PCA-FV with parametric weighting is lightly better than other methods.
This figure also shows that PCA-Gabor acts as a denoising mechanism reducing the noise in the PCs and thus representing more of the signal.
The PLCO study concluded that PCa-related mortality did not significantly differ between patients being screened or not [ 3].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com