ForeTiS

Subpackages

• ForeTiS.evaluation
  • ForeTiS.evaluation.eval_metrics
• ForeTiS.model
  • ForeTiS.model._additionalmodels
    • ForeTiS.model._additionalmodels.gpr_sklearn
    • ForeTiS.model._additionalmodels.lstmbayes_intel
    • ForeTiS.model._additionalmodels.mlpbayes_intel
  • ForeTiS.model._base_model
  • ForeTiS.model._baseline_model
  • ForeTiS.model._model_classes
  • ForeTiS.model._model_functions
  • ForeTiS.model._sklearn_model
  • ForeTiS.model._stat_model
  • ForeTiS.model._template_sklearn_model
  • ForeTiS.model._template_stat_model
  • ForeTiS.model._template_tensorflow_model
  • ForeTiS.model._template_torch_model
  • ForeTiS.model._tensorflow_model
  • ForeTiS.model._torch_model
  • ForeTiS.model.ard
  • ForeTiS.model.averagehistorical
  • ForeTiS.model.averagemoving
  • ForeTiS.model.averageseasonal
  • ForeTiS.model.averageseasonallag
  • ForeTiS.model.bayesridge
  • ForeTiS.model.elasticnet
  • ForeTiS.model.es
  • ForeTiS.model.gprtf
  • ForeTiS.model.lasso
  • ForeTiS.model.lstm
  • ForeTiS.model.lstmbayes
  • ForeTiS.model.mlp
  • ForeTiS.model.mlpbayes
  • ForeTiS.model.ridge
  • ForeTiS.model.sarima
  • ForeTiS.model.sarimax
  • ForeTiS.model.xgboost
• ForeTiS.optimization
  • ForeTiS.optimization.optuna_optim
• ForeTiS.postprocess
  • ForeTiS.postprocess.model_reuse
  • ForeTiS.postprocess.results_analysis
• ForeTiS.preprocess
  • ForeTiS.preprocess.DateCalenderFeatures
  • ForeTiS.preprocess.FeatureAdder
  • ForeTiS.preprocess.StatisticalFeatures
  • ForeTiS.preprocess.base_dataset
  • ForeTiS.preprocess.raw_data_functions
• ForeTiS.utils
  • ForeTiS.utils.check_functions
  • ForeTiS.utils.helper_functions

Submodules

• ForeTiS.optim_pipeline

Package Contents

ForeTiS.__version__ = 0.0.1

ForeTiS.__author__ = Josef Eiglsperger, Florian Haselbeck, Dominik G. Grimm

ForeTiS.__credits__ = GrimmLab @ TUM Campus Straubing (https://bit.cs.tum.de/)