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1.1.0 eventdetector_ts-1.1.0-py3-none-any.whl

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Project: eventdetector-ts
Version: 1.1.0
Filename: eventdetector_ts-1.1.0-py3-none-any.whl
Download: [link]
Size: 53358
MD5: 974e9f431b651e5ccec37898b16de6ab
SHA256: 6d89fefa4cc92461ec8a8c6b8c153d9001b47b02c5374d6c1af42044e484530c
Uploaded: 2023-11-28 15:31:29 +0000

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METADATA · WHEEL · RECORD

METADATA

Metadata-Version: 2.1
Name: eventdetector_ts
Version: 1.1.0
Summary: EventDetector introduces a universal event detection method for multivariate time series. Unlike traditional deep-learning methods, it's regression-based, requiring only reference events. The robust stacked ensemble, from Feed-Forward Neural Networks to Transformers, ensures accuracy by mitigating biases. The package supports practical implementation, excelling in detecting events with precision, validated across diverse domains.
Author-Email: Menouar Azib <menouar.azib[at]akkodis.com>
Maintainer-Email: Menouar Azib <menouar.azib[at]akkodis.com>
Project-Url: Bug Tracker, https://github.com/menouarazib/eventdetector/issues
Project-Url: Homepage, https://github.com/menouarazib/eventdetector
Keywords: Universal Event Detection,Multivariate Time Series,Regression-based,Stacked Ensemble Learning,Deep Learning Models,Feed-Forward Neural Networks,Transformers,Event Detection Package,Rare Events,Imbalanced Datasets,Anomaly Detection,Change Point Detection,Fraud Detection,Empirical Validations
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Requires-Dist: joblib
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: python_dateutil
Requires-Dist: scikit_learn
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: sympy
Requires-Dist: colorlog
Requires-Dist: pydot
Requires-Dist: pyqt5
Requires-Dist: tqdm
Description-Content-Type: text/markdown
[Description omitted; length: 37659 characters]

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