ADE                     Arbitrated Dynamic Ensemble
DETS                    Dynamic Ensemble for Time Series
base_ensemble           base_ensemble
build_base_ensemble     Wrapper for creating an ensemble
embed_timeseries        Embedding a Time Series
learning_base_models    Training the base models of an ensemble
meta_xgb_predict        Arbiter predictions via xgb
model_recent_performance
                        Recent performance of models using EMASE
model_specs             Setup base learning models
model_weighting         Model weighting
predict                 Predicting new observations using an ensemble
tsensembler             Dynamic Ensembles for Time Series Forecasting
update_ade              Updating an ADE model
update_ade_meta         Updating the metalearning layer of an ADE model
update_base_models      Update the base models of an ensemble
update_weights          Updating the weights of base models
water_consumption       Water Consumption in Oporto city (Portugal)
                        area.
xgb_optimizer           XGB optimizer
xgb_predict_            asdasd
