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Anomalienerkennung bei Zeitreihen

Identifizierung ungewöhnlicher Muster oder Ausreißer in Zeitreihendaten, die vom erwarteten Verhalten abweichen.

Leaderboard

Insgesamt 12 Modelle

Benchmarks

UCR Anomaly Archive
TimeVQVAE-AD
MSL
SMD
yelpchi
BOLT-GRAPH
SWaT
SMAP
PSM
amazon-fraud
cicids2017
OC-SVM / RF
NIPS-TS-SWAN
NIPS-TS-WATER
UCR-1
NIPS-TS-CREDITCARD
NIST Report of Test FR 4016
rTPNN
WADI
UCR-2
GECCO
Kaggle-Credit Card Fraud Dataset
DevNet
SMD_2-1
Synthetic
unsw-nb15
Edge-Detect-FRNN
NIPS_TS_Swan
SWAN
Yahoo A1
CARLA
WSD
Ozone
PoseR
Satellite
SIDD-Image
Segmented-FL
TODS
SMD_1-7
SMD_1-8
SMD_2-4
SMD_3-2
SMD_3-7
kdd
DNN-3
A2
A3
A4
A5
A6
A7
A8
A9
ASD
CCR
FDCompCN
SplitGNN
FishLarvae1
Heavy-haul Railway Tracks
HIT
NIPS-TS-GECCO
KDD21
KPI
KW51
Meerkat
MSL_P-14
MSL_P-15
NB15-Backdoor
DevNet
NF-CSE-CIC-IDS2018-v2
NF-CSE-CIC-IDS2018-v3
NF-UNSW-NB15-v2
NF-UNSW-NB15-v3
A1
NIPS_TS_Water