Principal component analysis (PCA) simplifies the complexity in high-dimensional data while retaining trends and patterns. It does this by transforming the data into fewer dimensions, which act as ...

Figure 2: PC scatterplots of the shape space of the lower molar of NR2 and other Hominins (left). The analysis combines the enamel–dentine junction (EDJ) and the cemento-enamel junction (CEJ). The ...

Abstract Principal component analysis (PCA) was employed to examine the effect of nutritional and bioactive compounds of legume milk chocolate as well as the sensory to document the extend of ...

Principal components analysis 3 key takeaways PCA is used to simplify complex datasets by reducing the number of dimensions without losing significant information. It identifies the directions ...

This article concerns the issue of data-driven fault diagnosis for series lithium-ion battery pack. A voltage correlation-based statistical analysis method is proposed. First, the voltage of each cell ...

Kahangwa, C. (2022) Application of Principal Component Analysis, Cluster Analysis, Pollution Index and Geoaccumulation Index in Pollution Assessment with Heavy Metals from Gold Mining Operations, ...