: Paléoclimatologie: principal component analysis

study method > statistical method > principal component analysis

principal component analysis

Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified. Principal component analysis has applications in many fields such as population genetics, microbiome studies, and atmospheric science. (Adapted from: https://en.wikipedia.org/wiki/Principal_component_analysis)

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