Glossary¶
There are many disciplines involved in the world of time series forecasting and many use different names for the same/similar things. To make it easier for further package navigation, these are important terms mentioned throughout the package.
Term |
Meaning |
Synonyms |
---|---|---|
Wrapper |
Convenient adapter to third party estimators following Sklearn API enabling time series forecasting |
|
Horizon |
Number of datapoints within defined data frequency that are predicted |
Steps-ahead |
Cross-validation |
Procedure to run model’s fitting and predicting on several test/train data splits in order to assess model ability to predict out-of-sample |
CV |
Split |
One of the train/test data subsamples (n_splits) created during Cross-validation (based on splitting strategy) |
|
Target |
Data we are trying to predict in form array_like, (1d) |
Target vector, Target variable, Dependent variable, Label, Response variable, Explained variable, Outcome variable, Output variable, Endogenous variable, Y |
Feature |
Measurable property (e.g. is_holiday) of the target (e.g. sales) in form of pandas.Dataframe |
Exogenous variable, Covariate, Regressor, Independent variable, Explanatory variable, Predictor variable, Input, X |