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Correlation vs. Covariance | Standardization of Data | with example in Python/NumPy | english

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The Multivariate Normal/Gaussian uses the Covariance Matrix to describe the interdependency of feature dimensions. Are the covariances in the off-diagonal elements related to correlation? In order to find it out, we need to standardize our data. Here are the notes: Here you can find an interactive web plot for the Multivariate Normal: It is common that multiple feature dimensions in high-dimensional data are not independent. Most of the time there is a linear relationship, called correlation. We can investigate it by looking at the correlation coefficients, i.e. the off-diagonal elements of the correlation matrix. This matrix is computed as the covariance matrix of standardized data. Standardization refers to the process of first centerin

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