NeuralTSNE.Utils.Preprocessing package

Subpackages

• NeuralTSNE.Utils.Preprocessing.Filters package
  • Submodules
  • NeuralTSNE.Utils.Preprocessing.Filters.filters module
    • filter_data_by_variance()
  • Module contents
• NeuralTSNE.Utils.Preprocessing.Normalizers package
  • Submodules
  • NeuralTSNE.Utils.Preprocessing.Normalizers.normalizers module
    • normalize_columns()
  • Module contents

Submodules

NeuralTSNE.Utils.Preprocessing.preprocessing module

prepare_data(variance_threshold: float, data: ndarray) → TensorView on GitHub

Prepare data for further analysis by filtering based on variance, saving means and variances, and normalizing columns.

Parameters:

• variance_threshold (float) – Threshold for variance-based feature selection.

• data (np.ndarray) – Input data array.

Returns:

Processed and normalized data tensor.

Return type:

torch.Tensor

Note

The function filters the input data based on the provided variance threshold, saves means and variances, and then normalizes the columns of the data before converting it into a torch.Tensor.

Module contents