Explained variance is a statistical measure that indicates how much of the total variance in a dataset can be attributed to a particular model or feature. In the context of data analysis and dimensionality reduction techniques, such as PCA, it helps in understanding the effectiveness of the components in capturing the underlying structure of the data.
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