Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

Original language	English
Title of host publication	PHM papers PROCEEDINGS 2020
Pages	1-10
Number of pages	10
Publication status	Published - 2020
Event	Prognostics and Health Management Europe - Duration: 27 Jul 2020 → 31 Jul 2020

Conference	Prognostics and Health Management Europe
Period	27/07/20 → 31/07/20

Research Field

@inproceedings{6d484b90f91d4894b140c51aef075333,

title = "Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study",

author = "Anahid Naghibzadeh-Jalali and Alexander Schindler and Bernhard Haslhofer and Andreas Rauber",

year = "2020",

language = "English",

isbn = "978-1-936263-32-5",

pages = "1--10",

booktitle = "PHM papers PROCEEDINGS 2020",

note = "Prognostics and Health Management Europe ; Conference date: 27-07-2020 Through 31-07-2020",

}

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

TY - GEN

T1 - Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study

A2 - Naghibzadeh-Jalali, Anahid

A2 - Schindler, Alexander

A2 - Haslhofer, Bernhard

A2 - Rauber, Andreas

PY - 2020

Y1 - 2020

M3 - Conference Proceedings with Oral Presentation

SN - 978-1-936263-32-5

SP - 1

EP - 10

BT - PHM papers PROCEEDINGS 2020

T2 - Prognostics and Health Management Europe

Y2 - 27 July 2020 through 31 July 2020

ER -