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Recent Releases of https://github.com/atrcheema/ai4water

https://github.com/atrcheema/ai4water - latest

Commits

  • ceea5ee: use python 3.9 (Ather Abbas) #37
  • f48af03: do not use mtropics for github (Ather Abbas) #37
  • bb0ad77: do not plot taylor plot on GA (Ather Abbas) #37

- Python
Published by github-actions[bot] about 3 years ago

https://github.com/atrcheema/ai4water - AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods

This package provides a python framework for building and testing machine learning models for time series and tabular data.

What's Changed

  • updated master with dev by @AtrCheema in https://github.com/AtrCheema/AI4Water/pull/12
  • Dev by @AtrCheema in https://github.com/AtrCheema/AI4Water/pull/13

Full Changelog: https://github.com/AtrCheema/AI4Water/compare/v1.0-beta...v1.0-beta.1 - predict method returns only predicted array by default. If the user wants true array as well, returntrue should be set to True. - changed name of sub-modules preprocessing => preprocessing, postprocessing => postprocessing, hyperopt => hyperopt and ETUtil => et - improved docs - removed bugs - transformations classes have config and fromconfig methods - integration of nbeats - added fitwith_tpot method for experiments - added autocorrelation and partial autocorrelation in eda - predict method does not receive prefix method - added examples - datahandler can read xlsx, csv, mat, npz, netcdf pqrquet and feather file types. - added regplot function as part of utils - predict method can calculate variety of errors. By default now calculates minimal errors - improved speed of tests and made them less verbose - unified ShapExplainer class for both ml and dl models - unified LimeExplainer class for both ml and dl models - Experiment class can handle verbosity argument better - improved interdependency of packages in different sub-modules i.e. shapfile not required if datasets sub-module is not used - pin the versions with which ai4water is tested - predict can take user defined arguments just as keras model or sklearn model - added conditionalize layer which is part of ConditionalRNN

- Python
Published by AtrCheema over 4 years ago

https://github.com/atrcheema/ai4water - AI4Water: a framework for building and testing machine learning models for hydrological simulations

This is beta release with some bugs fixed an docs improved.

- Python
Published by AtrCheema over 4 years ago