79 citations · 149 across the 9 of their papers we have counts for
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Mining Gamma-Ray Burst Data
Jon Hakkila, Richard J. Roiger, David J. Haglin +3
Gamma-ray bursts provide what is probably one of the messiest of all astrophysical data sets. Burst class properties are indistinct, as overlapping characteristics of individual bu…
A GRB Tool Shed
David J. Haglin, Richard J. Roiger, Jon Hakkila +2
We describe the design of a suite of software tools to allow users to query Gamma-Ray Burst (GRB) data and perform data mining expeditions. We call this suite of tools a shed (SHel…
Unsupervised Induction and Gamma-Ray Burst Classification
Richard J. Roiger, Jon Hakkila, David J. Haglin +2
We use ESX, a product of Information Acumen Corporation, to perform unsupervised learning on a data set containing 797 gamma-ray bursts taken from the BATSE 3B catalog. Assuming al…
The Fluence Duration Bias
Jon Hakkila, Charles A. Meegan, Geoffrey N. Pendleton +3
The fluence duration bias causes fluences and durations of faint gamma-ray bursts to be systematically underestimated relative to their peak fluxes. Using Monte Carlo analysis, we…
Properties of Gamma-Ray Burst Classes
Jon Hakkila, David J. Haglin, Richard J. Roiger +3
The three gamma-ray burst (GRB) classes identified by statistical clustering analysis (Mukherjee et al. 1998) are examined using the pattern recognition algorithm C4.5 (Quinlan 198…