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Observed since 21 Oct, 09:37 UTC
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Time series forecasting with Machine Learning and uncertainty quantification
A package for time series forecasting with Machine Learning and uncertainty quantification
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| Package / target | Requirement | Relationship |
|---|---|---|
matplotlibEnvironment{
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"marker": null,
"requires_python": ">=3.8",
"evaluation": "NOT_EVALUATED"
} | matplotlib | runtime |
numpyEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.8",
"evaluation": "NOT_EVALUATED"
} | numpy | runtime |
pandasEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.8",
"evaluation": "NOT_EVALUATED"
} | pandas | runtime |
rpy2Environment{
"extras": "",
"marker": null,
"requires_python": ">=3.8",
"evaluation": "NOT_EVALUATED"
} | rpy2 | runtime |
scikit-learnEnvironment{
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"requires_python": ">=3.8",
"evaluation": "NOT_EVALUATED"
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scipyEnvironment{
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"requires_python": ">=3.8",
"evaluation": "NOT_EVALUATED"
} | scipy | runtime |
bdist_wheel · 25.83 KB · Python py2.py3
sdist · 41.22 KB · Python source
Observed since 21 Oct, 09:37 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package_version:415935caa7c8b65f0bfe555316a0298dc3bf9fb1fc76e2107eca564a7f3bb4d1