Kernel centres semi-stratified selection without replacement #21
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- use np.random.choice to sample input data without replacement; - use np.percentile so samples are stratified with respect to (possibly multivariate) x values.
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Please note that all commits covered by this pull request are also included in #23 Aggregated pull request. |
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The pull request revises the way kernel centres are selected. The following changes have been introduced:
xvalues.I call this manner of centre selection semi-stratified, because the final result is concatenated independently from every column of the second array dimension, where indices are chosen randomly from quantiles returned by np.percentile.
Resolves the following issues: