Datasets:

hoangphihung442004
/

Audio_Features_ML_Results

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The dataset generation failed because of a cast error

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 17 new columns ({'Precision Val (Weighted)', 'F1-score Val (Macro)', 'Precision Test (Macro)', 'F1-score Test (Macro)', 'Recall Test (Macro)', 'Best Param', 'Tuning Time (s)', 'Recall Val (Macro)', 'Training Time (s)', 'Accuracy Test', 'Recall Test (Weighted)', 'Accuracy Val', 'Recall Val (Weighted)', 'Precision Val (Macro)', 'Precision Test (Weighted)', 'F1-score Test (Weighted)', 'F1-score Val (Weighted)'}) and 17 missing columns ({'Precision Val (Weighted) (Mean ± Std)', 'Precision Test (Weighted) (Mean ± Std)', 'F1-score Val (Macro) (Mean ± Std)', 'F1-score Val (Weighted) (Mean ± Std)', 'Folds Count', 'Recall Test (Weighted) (Mean ± Std)', 'Tuning Time (s) (Mean ± Std)', 'Recall Val (Weighted) (Mean ± Std)', 'Precision Val (Macro) (Mean ± Std)', 'F1-score Test (Weighted) (Mean ± Std)', 'Accuracy Test (Mean ± Std)', 'Training Time (s) (Mean ± Std)', 'Recall Test (Macro) (Mean ± Std)', 'Precision Test (Macro) (Mean ± Std)', 'F1-score Test (Macro) (Mean ± Std)', 'Accuracy Val (Mean ± Std)', 'Recall Val (Macro) (Mean ± Std)'}).

This happened while the csv dataset builder was generating data using

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'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_16000_pre_0.97_frame_256_nfft_256_hop_128_win_hamming_std_False_0712e423/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_22050_pre_0.97_frame_352_nfft_352_hop_176_win_hamming_std_False_08b1bbcd/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_22050_pre_0.97_frame_352_nfft_352_hop_176_win_hamming_std_False_08b1bbcd/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_22050_pre_0.97_frame_352_nfft_352_hop_176_win_hamming_std_False_08b1bbcd/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_22050_pre_0.97_frame_352_nfft_352_hop_176_win_hamming_std_False_08b1bbcd/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_22050_pre_0.97_frame_352_nfft_352_hop_176_win_hamming_std_False_08b1bbcd/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_22050_pre_0.97_frame_352_nfft_352_hop_176_win_hamming_std_False_08b1bbcd/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_44100_pre_0.97_frame_704_nfft_704_hop_352_win_hamming_std_False_f13b9ef3/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_44100_pre_0.97_frame_704_nfft_704_hop_352_win_hamming_std_False_f13b9ef3/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_44100_pre_0.97_frame_704_nfft_704_hop_352_win_hamming_std_False_f13b9ef3/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_44100_pre_0.97_frame_704_nfft_704_hop_352_win_hamming_std_False_f13b9ef3/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_44100_pre_0.97_frame_704_nfft_704_hop_352_win_hamming_std_False_f13b9ef3/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_44100_pre_0.97_frame_704_nfft_704_hop_352_win_hamming_std_False_f13b9ef3/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_48000_pre_0.97_frame_768_nfft_768_hop_384_win_hamming_std_False_dcc89626/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_48000_pre_0.97_frame_768_nfft_768_hop_384_win_hamming_std_False_dcc89626/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_48000_pre_0.97_frame_768_nfft_768_hop_384_win_hamming_std_False_dcc89626/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_48000_pre_0.97_frame_768_nfft_768_hop_384_win_hamming_std_False_dcc89626/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_48000_pre_0.97_frame_768_nfft_768_hop_384_win_hamming_std_False_dcc89626/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_48000_pre_0.97_frame_768_nfft_768_hop_384_win_hamming_std_False_dcc89626/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_64000_pre_0.97_frame_1024_nfft_1024_hop_512_win_hamming_std_False_7f1f0681/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_64000_pre_0.97_frame_1024_nfft_1024_hop_512_win_hamming_std_False_7f1f0681/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_64000_pre_0.97_frame_1024_nfft_1024_hop_512_win_hamming_std_False_7f1f0681/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_64000_pre_0.97_frame_1024_nfft_1024_hop_512_win_hamming_std_False_7f1f0681/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_64000_pre_0.97_frame_1024_nfft_1024_hop_512_win_hamming_std_False_7f1f0681/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_64000_pre_0.97_frame_1024_nfft_1024_hop_512_win_hamming_std_False_7f1f0681/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_8000_pre_0.97_frame_128_nfft_128_hop_64_win_hamming_std_False_f631d2ea/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_8000_pre_0.97_frame_128_nfft_128_hop_64_win_hamming_std_False_f631d2ea/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_8000_pre_0.97_frame_128_nfft_128_hop_64_win_hamming_std_False_f631d2ea/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_8000_pre_0.97_frame_128_nfft_128_hop_64_win_hamming_std_False_f631d2ea/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_8000_pre_0.97_frame_128_nfft_128_hop_64_win_hamming_std_False_f631d2ea/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_8000_pre_0.97_frame_128_nfft_128_hop_64_win_hamming_std_False_f631d2ea/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_96000_pre_0.97_frame_1536_nfft_1536_hop_768_win_hamming_std_False_581b23b0/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_96000_pre_0.97_frame_1536_nfft_1536_hop_768_win_hamming_std_False_581b23b0/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_96000_pre_0.97_frame_1536_nfft_1536_hop_768_win_hamming_std_False_581b23b0/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_96000_pre_0.97_frame_1536_nfft_1536_hop_768_win_hamming_std_False_581b23b0/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_96000_pre_0.97_frame_1536_nfft_1536_hop_768_win_hamming_std_False_581b23b0/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_pre_features/sr_96000_pre_0.97_frame_1536_nfft_1536_hop_768_win_hamming_std_False_581b23b0/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_128000_pre_TKEO_frame_2048_nfft_2048_hop_1024_win_hamming_std_False_e89952a9/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_128000_pre_TKEO_frame_2048_nfft_2048_hop_1024_win_hamming_std_False_e89952a9/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_128000_pre_TKEO_frame_2048_nfft_2048_hop_1024_win_hamming_std_False_e89952a9/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_128000_pre_TKEO_frame_2048_nfft_2048_hop_1024_win_hamming_std_False_e89952a9/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_128000_pre_TKEO_frame_2048_nfft_2048_hop_1024_win_hamming_std_False_e89952a9/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_128000_pre_TKEO_frame_2048_nfft_2048_hop_1024_win_hamming_std_False_e89952a9/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_256000_pre_TKEO_frame_4096_nfft_4096_hop_2048_win_hamming_std_False_dcb66021/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_256000_pre_TKEO_frame_4096_nfft_4096_hop_2048_win_hamming_std_False_dcb66021/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_256000_pre_TKEO_frame_4096_nfft_4096_hop_2048_win_hamming_std_False_dcb66021/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_256000_pre_TKEO_frame_4096_nfft_4096_hop_2048_win_hamming_std_False_dcb66021/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_256000_pre_TKEO_frame_4096_nfft_4096_hop_2048_win_hamming_std_False_dcb66021/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_256000_pre_TKEO_frame_4096_nfft_4096_hop_2048_win_hamming_std_False_dcb66021/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_64000_pre_TKEO_frame_1024_nfft_1024_hop_512_win_hamming_std_False_e1c5e7f6/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_64000_pre_TKEO_frame_1024_nfft_1024_hop_512_win_hamming_std_False_e1c5e7f6/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_64000_pre_TKEO_frame_1024_nfft_1024_hop_512_win_hamming_std_False_e1c5e7f6/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_64000_pre_TKEO_frame_1024_nfft_1024_hop_512_win_hamming_std_False_e1c5e7f6/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_64000_pre_TKEO_frame_1024_nfft_1024_hop_512_win_hamming_std_False_e1c5e7f6/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_64000_pre_TKEO_frame_1024_nfft_1024_hop_512_win_hamming_std_False_e1c5e7f6/fold_04/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/cv_summary.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_04/result.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 784, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Model: string
              Feature: string
              Number Feature: int64
              Tuning Time (s): double
              Training Time (s): double
              Precision Val (Weighted): double
              Recall Val (Weighted): double
              F1-score Val (Weighted): double
              Accuracy Val: double
              Precision Val (Macro): double
              Recall Val (Macro): double
              F1-score Val (Macro): double
              Precision Test (Weighted): double
              Recall Test (Weighted): double
              F1-score Test (Weighted): double
              Accuracy Test: double
              Precision Test (Macro): double
              Recall Test (Macro): double
              F1-score Test (Macro): double
              Best Param: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2996
              to
              {'Model': Value('string'), 'Feature': Value('string'), 'Number Feature': Value('int64'), 'Folds Count': Value('int64'), 'Tuning Time (s) (Mean ± Std)': Value('string'), 'Training Time (s) (Mean ± Std)': Value('string'), 'Precision Val (Weighted) (Mean ± Std)': Value('string'), 'Recall Val (Weighted) (Mean ± Std)': Value('string'), 'F1-score Val (Weighted) (Mean ± Std)': Value('string'), 'Accuracy Val (Mean ± Std)': Value('string'), 'Precision Val (Macro) (Mean ± Std)': Value('string'), 'Recall Val (Macro) (Mean ± Std)': Value('string'), 'F1-score Val (Macro) (Mean ± Std)': Value('string'), 'Precision Test (Weighted) (Mean ± Std)': Value('string'), 'Recall Test (Weighted) (Mean ± Std)': Value('string'), 'F1-score Test (Weighted) (Mean ± Std)': Value('string'), 'Accuracy Test (Mean ± Std)': Value('string'), 'Precision Test (Macro) (Mean ± Std)': Value('string'), 'Recall Test (Macro) (Mean ± Std)': Value('string'), 'F1-score Test (Macro) (Mean ± Std)': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 17 new columns ({'Precision Val (Weighted)', 'F1-score Val (Macro)', 'Precision Test (Macro)', 'F1-score Test (Macro)', 'Recall Test (Macro)', 'Best Param', 'Tuning Time (s)', 'Recall Val (Macro)', 'Training Time (s)', 'Accuracy Test', 'Recall Test (Weighted)', 'Accuracy Val', 'Recall Val (Weighted)', 'Precision Val (Macro)', 'Precision Test (Weighted)', 'F1-score Test (Weighted)', 'F1-score Val (Weighted)'}) and 17 missing columns ({'Precision Val (Weighted) (Mean ± Std)', 'Precision Test (Weighted) (Mean ± Std)', 'F1-score Val (Macro) (Mean ± Std)', 'F1-score Val (Weighted) (Mean ± Std)', 'Folds Count', 'Recall Test (Weighted) (Mean ± Std)', 'Tuning Time (s) (Mean ± Std)', 'Recall Val (Weighted) (Mean ± Std)', 'Precision Val (Macro) (Mean ± Std)', 'F1-score Test (Weighted) (Mean ± Std)', 'Accuracy Test (Mean ± Std)', 'Training Time (s) (Mean ± Std)', 'Recall Test (Macro) (Mean ± Std)', 'Precision Test (Macro) (Mean ± Std)', 'F1-score Test (Macro) (Mean ± Std)', 'Accuracy Val (Mean ± Std)', 'Recall Val (Macro) (Mean ± Std)'}).
              
              This happened while the csv dataset builder was generating data using
              
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'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_00/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_01/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_02/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_03/result.csv', 'hf://datasets/hoangphihung442004/Audio_Features_ML_Results@5787981e3d6f158f13c43e6270682c90f5f5c373/stft_tkeo_pre_features/sr_96000_pre_TKEO_frame_1536_nfft_1536_hop_768_win_hamming_std_False_2881a8c4/fold_04/result.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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Model string	Feature string	Number Feature int64	Folds Count int64	Tuning Time (s) (Mean ± Std) string	Training Time (s) (Mean ± Std) string	Precision Val (Weighted) (Mean ± Std) string	Recall Val (Weighted) (Mean ± Std) string	F1-score Val (Weighted) (Mean ± Std) string	Accuracy Val (Mean ± Std) string	Precision Val (Macro) (Mean ± Std) string	Recall Val (Macro) (Mean ± Std) string	F1-score Val (Macro) (Mean ± Std) string	Precision Test (Weighted) (Mean ± Std) string	Recall Test (Weighted) (Mean ± Std) string	F1-score Test (Weighted) (Mean ± Std) string	Accuracy Test (Mean ± Std) string	Precision Test (Macro) (Mean ± Std) string	Recall Test (Macro) (Mean ± Std) string	F1-score Test (Macro) (Mean ± Std) string
LR	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	5	3.6844 ± 1.4663	1.7517 ± 0.2860	0.3904 ± 0.0278	0.3875 ± 0.0071	0.3083 ± 0.0073	0.3875 ± 0.0071	0.3948 ± 0.0331	0.3410 ± 0.0062	0.2787 ± 0.0067	0.3964 ± 0.0183	0.3924 ± 0.0041	0.3120 ± 0.0044	0.3924 ± 0.0041	0.3993 ± 0.0229	0.3453 ± 0.0039	0.2818 ± 0.0046
KNN	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	5	8.8689 ± 0.3723	0.0178 ± 0.0031	0.6790 ± 0.0082	0.6812 ± 0.0082	0.6797 ± 0.0083	0.6812 ± 0.0082	0.6764 ± 0.0083	0.6777 ± 0.0084	0.6766 ± 0.0084	0.6742 ± 0.0075	0.6767 ± 0.0072	0.6751 ± 0.0074	0.6767 ± 0.0072	0.6716 ± 0.0076	0.6721 ± 0.0070	0.6715 ± 0.0074
SVM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	5	99.7373 ± 2.5831	7.3137 ± 0.1940	0.4591 ± 0.0238	0.4624 ± 0.0178	0.3917 ± 0.0305	0.4624 ± 0.0178	0.4572 ± 0.0263	0.4123 ± 0.0193	0.3591 ± 0.0324	0.4597 ± 0.0270	0.4622 ± 0.0179	0.3907 ± 0.0309	0.4622 ± 0.0179	0.4592 ± 0.0289	0.4120 ± 0.0194	0.3581 ± 0.0328
RF	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	5	61.3920 ± 6.0727	0.8815 ± 0.2605	0.6938 ± 0.0046	0.6950 ± 0.0048	0.6928 ± 0.0048	0.6950 ± 0.0048	0.6969 ± 0.0048	0.6871 ± 0.0059	0.6903 ± 0.0056	0.6849 ± 0.0056	0.6859 ± 0.0053	0.6835 ± 0.0051	0.6859 ± 0.0053	0.6887 ± 0.0066	0.6774 ± 0.0046	0.6810 ± 0.0050
ET	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	5	36.1728 ± 1.8717	0.4150 ± 0.1439	0.6818 ± 0.0180	0.6817 ± 0.0177	0.6787 ± 0.0194	0.6817 ± 0.0177	0.6865 ± 0.0180	0.6707 ± 0.0208	0.6752 ± 0.0211	0.6784 ± 0.0116	0.6781 ± 0.0128	0.6744 ± 0.0140	0.6781 ± 0.0128	0.6840 ± 0.0098	0.6660 ± 0.0146	0.6707 ± 0.0142
LGBM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	5	90.5261 ± 12.0875	1.7096 ± 0.2863	0.6826 ± 0.0085	0.6836 ± 0.0090	0.6826 ± 0.0084	0.6836 ± 0.0090	0.6830 ± 0.0101	0.6796 ± 0.0079	0.6808 ± 0.0084	0.6775 ± 0.0053	0.6781 ± 0.0051	0.6774 ± 0.0053	0.6781 ± 0.0051	0.6780 ± 0.0052	0.6736 ± 0.0058	0.6753 ± 0.0052
LR	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_frame_4096_nfft_4096_hop_2048_win_hamming_chroma_12_std_False_6946d62a	12	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	5	42.8158 ± 14.4045	14.5938 ± 3.3958	0.5437 ± 0.0067	0.5541 ± 0.0062	0.5390 ± 0.0062	0.5541 ± 0.0062	0.5399 ± 0.0073	0.5367 ± 0.0069	0.5287 ± 0.0070	0.5432 ± 0.0053	0.5538 ± 0.0049	0.5396 ± 0.0048	0.5538 ± 0.0049	0.5395 ± 0.0060	0.5374 ± 0.0053	0.5298 ± 0.0056
KNN	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	5	192.0724 ± 10.4552	0.0926 ± 0.0871	0.7371 ± 0.0070	0.7388 ± 0.0068	0.7377 ± 0.0069	0.7388 ± 0.0068	0.7396 ± 0.0076	0.7395 ± 0.0078	0.7394 ± 0.0077	0.7313 ± 0.0063	0.7325 ± 0.0068	0.7317 ± 0.0064	0.7325 ± 0.0068	0.7337 ± 0.0067	0.7318 ± 0.0070	0.7325 ± 0.0067
SVM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	5	236.8441 ± 15.7628	18.5432 ± 13.4787	0.6194 ± 0.0382	0.6206 ± 0.0343	0.6108 ± 0.0360	0.6206 ± 0.0343	0.6227 ± 0.0425	0.6081 ± 0.0357	0.6066 ± 0.0389	0.6158 ± 0.0389	0.6171 ± 0.0359	0.6075 ± 0.0367	0.6171 ± 0.0359	0.6182 ± 0.0431	0.6049 ± 0.0362	0.6030 ± 0.0389
RF	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	5	166.5489 ± 17.2444	2.7252 ± 0.9786	0.7296 ± 0.0069	0.7300 ± 0.0064	0.7259 ± 0.0067	0.7300 ± 0.0064	0.7375 ± 0.0073	0.7244 ± 0.0061	0.7272 ± 0.0067	0.7212 ± 0.0066	0.7219 ± 0.0063	0.7173 ± 0.0063	0.7219 ± 0.0063	0.7285 ± 0.0067	0.7156 ± 0.0055	0.7179 ± 0.0059
ET	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	5	46.9076 ± 1.0835	1.2091 ± 0.6045	0.7244 ± 0.0153	0.7245 ± 0.0155	0.7205 ± 0.0161	0.7245 ± 0.0155	0.7325 ± 0.0153	0.7186 ± 0.0159	0.7216 ± 0.0163	0.7226 ± 0.0113	0.7227 ± 0.0107	0.7185 ± 0.0115	0.7227 ± 0.0107	0.7305 ± 0.0113	0.7158 ± 0.0113	0.7190 ± 0.0117
LGBM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	5	141.8534 ± 12.9230	2.7874 ± 0.7639	0.7474 ± 0.0067	0.7484 ± 0.0057	0.7474 ± 0.0060	0.7484 ± 0.0057	0.7526 ± 0.0087	0.7488 ± 0.0049	0.7501 ± 0.0065	0.7450 ± 0.0096	0.7470 ± 0.0096	0.7454 ± 0.0093	0.7470 ± 0.0096	0.7497 ± 0.0104	0.7472 ± 0.0084	0.7479 ± 0.0091
LR	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_pre_0.97_hop_2048_win_hamming_bins_126_bpo_12_std_False_8f379c90	126	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	5	247.5095 ± 21.6216	197.7080 ± 27.4608	0.3814 ± 0.0085	0.3926 ± 0.0078	0.3293 ± 0.0075	0.3926 ± 0.0078	0.3795 ± 0.0078	0.3484 ± 0.0068	0.3003 ± 0.0072	0.3828 ± 0.0128	0.3941 ± 0.0069	0.3300 ± 0.0082	0.3941 ± 0.0069	0.3809 ± 0.0152	0.3498 ± 0.0064	0.3010 ± 0.0075
KNN	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	5	661.3835 ± 21.6590	0.0259 ± 0.0014	0.4764 ± 0.0068	0.4793 ± 0.0064	0.4737 ± 0.0070	0.4793 ± 0.0064	0.4711 ± 0.0076	0.4679 ± 0.0068	0.4658 ± 0.0075	0.4744 ± 0.0084	0.4767 ± 0.0084	0.4712 ± 0.0083	0.4767 ± 0.0084	0.4703 ± 0.0094	0.4659 ± 0.0075	0.4641 ± 0.0081
SVM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	5	266.1343 ± 14.1786	110.3508 ± 12.4052	0.3427 ± 0.0289	0.3335 ± 0.0112	0.2575 ± 0.0339	0.3335 ± 0.0112	0.3230 ± 0.0328	0.2959 ± 0.0153	0.2363 ± 0.0366	0.3428 ± 0.0350	0.3333 ± 0.0104	0.2567 ± 0.0348	0.3333 ± 0.0104	0.3232 ± 0.0393	0.2959 ± 0.0156	0.2358 ± 0.0378
RF	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	5	1048.7438 ± 101.0432	10.6422 ± 2.2254	0.4865 ± 0.0144	0.4610 ± 0.0064	0.4134 ± 0.0070	0.4610 ± 0.0064	0.4947 ± 0.0197	0.4187 ± 0.0056	0.3892 ± 0.0070	0.4693 ± 0.0113	0.4515 ± 0.0026	0.4021 ± 0.0051	0.4515 ± 0.0026	0.4762 ± 0.0153	0.4097 ± 0.0020	0.3779 ± 0.0065
ET	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	5	1129.5883 ± 412.0766	28.8366 ± 15.2577	0.4896 ± 0.0145	0.4788 ± 0.0116	0.4389 ± 0.0145	0.4788 ± 0.0116	0.4938 ± 0.0158	0.4409 ± 0.0127	0.4187 ± 0.0156	0.4800 ± 0.0082	0.4740 ± 0.0033	0.4341 ± 0.0069	0.4740 ± 0.0033	0.4820 ± 0.0088	0.4365 ± 0.0052	0.4137 ± 0.0087
LGBM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	5	1664.8276 ± 517.7478	26.5540 ± 11.9806	0.4789 ± 0.0054	0.4868 ± 0.0049	0.4678 ± 0.0112	0.4868 ± 0.0049	0.4765 ± 0.0063	0.4603 ± 0.0115	0.4524 ± 0.0146	0.4657 ± 0.0065	0.4757 ± 0.0067	0.4558 ± 0.0043	0.4757 ± 0.0067	0.4630 ± 0.0083	0.4499 ± 0.0066	0.4407 ± 0.0071
LR	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
ET	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LGBM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
LR	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
KNN	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
SVM	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null
RF	sr_256000_nfft_4096_pre_0.97_b9db273d	2,049	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null

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Audio Features ML Results

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