Quality Metrics for Principal Components Analysis

Given the results of the PCA algorithm, data set of eigenvalues in decreasing order, full number of principal components p and reduced number of components p rp the problem is to evaluate the explained variances radio and noise variance.

QualityMetricsId for the PCA algorithm is explainedVarianceMetrics.

For description of the default PCA quality metrics, refer to Details.

For more complete information about compiler optimizations, see our Optimization Notice.
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