Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

P. MishraExplainable AI Recipes https://doi.org/10.1007/978-1-4842-9029-3_6

6. Explainability for Time-Series Models

Pradeepta Mishra¹  

(1)

Bangalore, Karnataka, India

 

A time series, as the name implies, has a time stamp and a variable that we are observing over time, such as stock prices, sales, revenue, profit over time, etc. Time-series modeling is a set of techniques that can be used to generate multistep predictions for a future time period, which will help a business to plan better and will help decision-makers to plan according to the future estimations. There are machine learning–based techniques that can be applied to generate future forecasting; ...