Unblinded Data for PLAsTiCC Classification Challenge

Modelers, PLASTICC; Narayan, Gautham; Kessler, Richard

doi:10.5281/zenodo.2535746

Title: Unblinded Data for PLAsTiCC Classification Challenge

Dataset
Other Related Research

Abstract

For classification challenge (https://plasticc.org), the unblinded data files are included here. See PDF note above for more information. The original challenge (Sep 28, 2018 - Dec 17, 2018) was hosted at https://www.kaggle.com/c/PLAsTiCC-2018 .

Authors:: Modelers, PLASTICC; Narayan, Gautham; Kessler, Richard

Publication Date:: Mon Jan 21 04:00:00 UTC 2019

DOE Contract Number:: AC02-76SF00515; AC02-05CH11231

Research Org.:: SLAC National Accelerator Lab., Menlo Park, CA (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

Collaborations:: PLASTICC Team; PLASTICC Modelers

Subject:: 79 ASTRONOMY AND ASTROPHYSICS; astronomy; classification; simulation; transients

OSTI Identifier:: 1872199

DOI:: https://doi.org/10.5281/zenodo.2535746

Citation Formats


                    Modelers, PLASTICC, Narayan, Gautham, and Kessler, Richard. Unblinded Data for PLAsTiCC Classification Challenge.  United States: N. p., 2019. 
        Web.  doi:10.5281/zenodo.2535746.

Copy to clipboard


                    Modelers, PLASTICC, Narayan, Gautham, & Kessler, Richard. Unblinded Data for PLAsTiCC Classification Challenge.  United States.  doi:https://doi.org/10.5281/zenodo.2535746

Copy to clipboard


                    Modelers, PLASTICC, Narayan, Gautham, and Kessler, Richard. 2019.  
"Unblinded Data for PLAsTiCC Classification Challenge".  United States.  doi:https://doi.org/10.5281/zenodo.2535746.  https://www.osti.gov/servlets/purl/1872199. Pub date:Mon Jan 21 04:00:00 UTC 2019

Copy to clipboard


                    
@article{osti_1872199,

  title        = {Unblinded Data for PLAsTiCC Classification Challenge},

  author       = {Modelers, PLASTICC and Narayan, Gautham and Kessler, Richard},

  abstractNote = {For classification challenge (https://plasticc.org), the unblinded data files are included here. See PDF note above for more information. The original challenge (Sep 28, 2018 - Dec 17, 2018) was hosted at https://www.kaggle.com/c/PLAsTiCC-2018 .},

  doi          = {10.5281/zenodo.2535746},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Jan 21 04:00:00 UTC 2019},

  month        = {Mon Jan 21 04:00:00 UTC 2019}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.5281/zenodo.2535746

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

Metadata Classification Machine Learning Data

Dataset Collier, Hannah ; Enright, Eric

This GitLab project contains the training data that was used for the metadata machine learning classification project.
Wave Classification Statistical Data for US Waters

Dataset Haas, Kevin

Wave statistics computed using output from the NOAA WWIII hindcast simulations, spanning thirty years from 1980 to 2009. The statistics are computed based on frequency-directional variance density spectra every three hours for 1951 locations in US waters.
VULCAN temperature dataset for SMC data challenge

Dataset Peterson, Peter

The VULCAN Beamline dataset provides the sample measurement, where temperatures is recorded in two physically different places on the sample. These are held in two different hdf5 groups in the data file.
ARM: WSI: cloud and aerosol info, classification summary data

Dataset Flynn, Connor

WSI: cloud and aerosol info, classification summary data
Neutron Imaging dataset for SMC 2021 data challenge

Dataset Peterson, Peter ; Granroth, Garrett ; Bilheux, Hassina ; ...

The neutron radiography (nR) dataset provides information of the neutron events as measured for the Siemens star mask using the Timepix3 detector. The recordings consist of the position (x and y axes), the time-stamp, and time-over-threshold (TOT) values of each neutron event.

Similar Records