NeuralTSNE.Utils.Preprocessing.Filters package

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NeuralTSNE.Utils.Preprocessing.Filters.filters module

filter_data_by_variance(data: Tensor, variance_threshold: float) → Tensor | NoneView on GitHub

Filter columns of a 2D torch.Tensor based on the variance of each column.

If the variance_threshold is None, the function returns None, indicating no filtering is performed.

Parameters:

• data (torch.Tensor) – The input 2D tensor with columns to be filtered.

• variance_threshold (float) – The threshold for column variance. Columns with variance below this threshold will be filtered out.

Returns:

If variance_threshold is None, returns None. Otherwise, returns a new tensor with columns filtered based on variance.

Return type:

torch.Tensor | None

Note

• If variance_threshold is set to None, the function returns None, and no filtering is performed.

• The function filters columns based on the variance of each column, keeping only those with variance greater than the specified threshold.

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