A comparison of statistical learning methods for deriving determining factors of accident occurrence from an imbalanced high resolution dataset

Matthias Schlögl; Rainer Stütz; Gregor Laaha; Michael Melcher

A comparison of statistical learning methods for deriving determining factors of accident occurrence from an imbalanced high resolution dataset

Matthias Schlögl, Rainer Stütz, Gregor Laaha, Michael Melcher

Transportation Infrastructure Technologies

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	134-149
Number of pages	16
Journal	Accident Analysis and Prevention
Volume	127
Issue number	127
Publication status	Published - 2019

Research Field

Former Research Field - Mobility Systems

Cite this

@article{0821379193304d98862c678fdb0e83b8,

title = "A comparison of statistical learning methods for deriving determining factors of accident occurrence from an imbalanced high resolution dataset",

author = "Matthias Schl{\"o}gl and Rainer St{\"u}tz and Gregor Laaha and Michael Melcher",

year = "2019",

language = "English",

volume = "127",

pages = "134--149",

journal = "Accident Analysis and Prevention",

issn = "0001-4575",

publisher = "Elsevier Ltd.",

number = "127",

}

TY - JOUR

T1 - A comparison of statistical learning methods for deriving determining factors of accident occurrence from an imbalanced high resolution dataset

AU - Schlögl, Matthias

AU - Stütz, Rainer

AU - Laaha, Gregor

AU - Melcher, Michael

PY - 2019

Y1 - 2019

M3 - Article

SN - 0001-4575

VL - 127

SP - 134

EP - 149

JO - Accident Analysis and Prevention

JF - Accident Analysis and Prevention

IS - 127

ER -