jura
OpenML dataset with id 41479
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/21230436/jura.arff
Upload date: 14 March 2019
Dataset Characteristics
Number of features: 18 (numeric: 18, symbolic: 0 and in total binary: 0 )
Number of instances: 359
Number of instances with missing values: 0
Number of missing values: 0
Multivariate regression data set from: https://link.springer.com/article/10.1007%2Fs10994-016-5546-z : The Jura (Goovaerts 1997) dataset consists of measurements of concentrations of seven heavy metals (cadmium, cobalt, chromium, copper, nickel, lead, and zinc), recorded at 359 locations in the topsoil of a region of the Swiss Jura. The type of land use (Forest, Pasture, Meadow, Tillage) and rock type (Argovian, Kimmeridgian, Sequanian, Portlandian, Quaternary) were also recorded for each location. In a typical scenario (Goovaerts 1997; Alvarez and Lawrence 2011), we are interested in the prediction of the concentration of metals that are more expensive to measure (primary variables) using measurements of metals that are cheaper to sample (secondary variables). In this study, cadmium, copper and lead are treated as target variables while the remaining metals along with land use type, rock type and the coordinates of each location are used as predictive features.
This page was built for dataset: jura
