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eeg-ml-pipeline

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0.4 eeg_ml_pipeline-0.4-py3-none-any.whl
0.3 eeg_ml_pipeline-0.3-py3-none-any.whl
0.2 eeg_ml_pipeline-0.2-py3-none-any.whl
0.1 eeg_ml_pipeline-0.1-py3-none-any.whl

Wheel Details

Project: eeg-ml-pipeline
Version: 0.1
Filename: eeg_ml_pipeline-0.1-py3-none-any.whl
Download: [link]
Size: 18866
MD5: d5480171cd20a44fa2209020bd9fe784
SHA256: 37afe145ede3ea5b0409335a72887a41a7bb3f70daeb1fb9f1595400adae7fa7
Uploaded: 2024-11-24 01:45:04 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: eeg-ml-pipeline
Version: 0.1
Summary: A Python package for EEG machine learning analysis, classification, and visualization.
Author: Yossef Emara
Author-Email: emara004[at]umn.edu
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: pandas (>=2.0.0)
Requires-Dist: scipy
Requires-Dist: mne
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: antropy
Requires-Dist: featurewiz
Requires-Dist: imblearn
Requires-Dist: tensorflow
Requires-Dist: dask[dataframe] (>=2021.9.1)
Requires-Dist: pyts
Requires-Dist: librosa
Requires-Dist: torch
Requires-Dist: PyWavelets
Requires-Dist: re
License-File: LICENSE
[No description]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.41.2)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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eeg_ml_pipeline/config.py sha256=lTB0AvpHRIlbn0zgzpJZcSAeKt6DiknQCZZClhSplCI 4663
eeg_ml_pipeline/entropy_features.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
eeg_ml_pipeline/feature_extraction.py sha256=OudBKEZVafykqD7y-ZEDWAYoC_EID3bp3mjC7K_C7qw 4002
eeg_ml_pipeline/fractal_dimensions_features.py sha256=e6FbsC8Itr-Zx-CXx26w7rJkFpwvjzZazX1SUmViwsI 856
eeg_ml_pipeline/frequency_features.py sha256=AWB7wHLO-uEar4e-K-GV78_x-y3CVzoQzBbrqIBNZAA 4523
eeg_ml_pipeline/model_training.py sha256=ZfJJEFMHx3Vbwr_xo4s6e1QagmiuzBGRsbnSD95SPlI 11724
eeg_ml_pipeline/pipeline.py sha256=EbeoRKLdKFezRr0HFphmjn-N6YXD_FCbo2JppV0y8a8 14932
eeg_ml_pipeline/time_features.py sha256=2z1xY08LLOwiJqQPPO0xGrLMoKWY6qquwkq3E7Zo7Jg 1720
eeg_ml_pipeline/utils.py sha256=8uTWmIgwk959Hglcm3gyJP9vYRJ1yhzVsmF1EDCPZwE 8175
eeg_ml_pipeline/visualization.py sha256=tu23POxWzAi2zyLUfrW1d3K2G1OPt9QaSid7dnp5BfE 1819
eeg_ml_pipeline/wavelet_features.py sha256=91e7JMbkhM0svvX8w2NZ_oKTe0w65gfg6AuMrRDErIU 749
eeg_ml_pipeline-0.1.dist-info/LICENSE sha256=Io5LarYoshJTXykzQbatM_xDpa7V60_086vu87LHIqo 1090
eeg_ml_pipeline-0.1.dist-info/METADATA sha256=ejqJApILItEP8N6C_NTKyxxBLaAUs8PAqUa-KSPEb74 843
eeg_ml_pipeline-0.1.dist-info/WHEEL sha256=yQN5g4mg4AybRjkgi-9yy4iQEFibGQmlz78Pik5Or-A 92
eeg_ml_pipeline-0.1.dist-info/top_level.txt sha256=h-zHQ21tH2plc7l2W-MGqvUW80LlghJwoqBbSXs49Wc 16
eeg_ml_pipeline-0.1.dist-info/RECORD — —

top_level.txt

eeg_ml_pipeline