2014-01-20T20:08:40Z Public 0 ozone_level ozone_level public ARFF active 2014-01-20T20:08:40Z 1 https://www.openml.org/data/download/52202/ozone_level.arff 1 **Author**: **Source**: Unknown - **Please cite**: 1. Title: Ozone Level Detection 2. Source: Kun Zhang zhang.kun05 '@' gmail.com Department of Computer Science, Xavier University of Lousiana Wei Fan wei.fan '@' gmail.com IBM T.J.Watson Research XiaoJing Yuan xyuan '@' uh.edu Engineering Technology Department, College of Technology, University of Houston 3. Past Usage: Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond, Knowledge and Information Systems, Vol. 14, No. 3, 2008. Discusses details about the dataset, its use as well as various experiments (both cross-validation and streaming) using many state-of-the-art methods. A shorter version of the paper (does not contain some detailed experiments as the journal paper above) is in: Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions. ICDM 2006: 753-764 4. Relevant Information: The following are specifications for several most important attributes that are highly valued by Texas Commission on Environmental Quality (TCEQ). More details can be found in the two relevant papers. -- O 3 - Local ozone peak prediction -- Upwind - Upwind ozone background level -- EmFactor - Precursor emissions related factor -- Tmax - Maximum temperature in degrees F -- Tb - Base temperature where net ozone production begins (50 F) -- SRd - Solar radiation total for the day -- WSa - Wind speed near sunrise (using 09-12 UTC forecast mode) -- WSp - Wind speed mid-day (using 15-21 UTC forecast mode) 5. Number of Instances: 2536 6. Number of Attributes: 73 7. Attribute Information: 1,0 | two classes 1: ozone day, 0: normal day Class 0