XAI Evaluation Multivariate Time Series Dataset

This data repository comprises three distinct datasets tailored for different predictive modeling tasks. The first dataset is a synthetic dataset designed to simulate multivariate time series patterns, incorporating both linear and non-linear dependencies among input and target features. The second dataset, the Beijing Air Quality PM2.5 dataset, consists of PM2.5 measurements alongside meteorological data like temperature, humidity, and wind speed, with the objective of predicting PM2.5 concentrations. Lastly, the Beijing Multi-Site Air Quality dataset encompasses hourly readings of various air pollutants from 12 monitoring sites in Beijing, aiming to estimate PM2.5 pollutant levels in the atmosphere. Each dataset presents unique challenges and opportunities for developing and evaluating predictive models, offering valuable resources for research and analysis in environmental science and machine learning domains.