Add explained variance based scheduler #104
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nailimixaM
approved these changes
Mar 1, 2024
| cum_var = np.cumsum(np.array(eigen_vals)) / np.sum(eigen_vals) | ||
| dim = np.argmax(cum_var > 1 - self.uev_threshold) | ||
| dim -= dim % self.round_interval | ||
| dim = int(dim) |
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Is it worth having the round_interval parameter passed to slicing schedulers in general, to ensure they always return dims that are rounded accordingly? I guess the constant and function schedulers could ask for constants/functions that take the rounding interval into account already, but what about this scheduler?
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Add a new slicing scheduler that is based on the cumulative explained variance from the PCA. Includes a cleanup of the dimensions handling methods.