divina¶
Date: Nov 30, 2021 Version:
Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support
divina
is an open source, BSD3-licensed library providing scalable and hyper-interpretable causal forecasting capabilities written in Python and consumable via CLI.
The aim of divina
is to deliver performance-oriented and hypter-interpretable exogenous time series forecasting models by producing accurate and bootstrapped predictions, local and overridable factor summaries and easily configurable feature engineering and experiment management capabilities.
Installation¶
divina
is available via pypi and can be install using the python package manager pip as shown below.
pip install divina
Getting Started¶
To run an experiment with divina, first install it and then create an experiment definition that describes your experiment. Here we create a minimal experiment definition that allows us to run a forecasting experiment using the retail sales and time data included with divina.
{
"experiment_definition": {
"target": "Sales",
"time_index": "Date",
"data_path": "divina://retail_sales"
}
}