| Description: | This dataset is from a 2018 Kaggle competition. The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022. LSST will revolutionize our understanding of the changing sky, discovering and measuring millions of time-varying objects. PLAsTiCCis a large data challenge for which participants are asked to classify astronomical time series data. These simulated time series, or ‘light curves’ are measurements of an object’s brightness as a function of time - by measuring the photon flux in six different astronomical filters (commonly referred to as passbands). These passbands includeultra-violet, optical and infrared regions of the light spectrum. There are many different types of astronomical objects (that are driven by different physical processes) that we sep-arate into astronomical classes. This arff represents a snap shot of the data available and is created from the train set published in the aforemention competition. 36 dimension was chosen as it represents a value at which most instances would not be truncated. |
