ThermalPowerConsumptionMarsExpress60
OpenML dataset with id 45716
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22117239/ThermalPowerConsumptionMarsExpress60.arff
Upload date: 11 January 2024
Dataset Characteristics
Number of features: 518 (numeric: 518, symbolic: 0 and in total binary: 0 )
Number of instances: 65,952
Number of instances with missing values: 5,859
Number of missing values: 331,128
The data, in terms of context data and thermal power consumption measurements, capture the status of the spacecraft over four Martian years sampled at six different time resolutions ranging from 1 min to 60 min. Here we present the dataset with 60 min time resolution, while other time resolutions can be obtained following the link in the publication. From a data analysis point-of-view, analysing these data presents great challenges - even for the more sophisticated state-of-the-art artificial intelligence methods. In particular, given the heterogeneity, complexity and magnitude of the data, they can be employed in different scenarios and analysed through the prism of a variety of machine learning tasks, such as multi-target regression, learning from data streams, anomaly detection, clustering etc. While analysing MEX"s telemetry data is critical for aiding very important decisions regarding the spacecraft status, it can be used to extract novel knowledge and monitor the spacecrafts" health, but also to benchmark artificial intelligence methods designed for a variety of tasks.
This page was built for dataset: ThermalPowerConsumptionMarsExpress60
