Published on 21 January 2021

Establishing diversity in synthetic time series for prediction performance evaluation

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Fouad, Bahrpeyma;Mark, Roantree;Paolo, Cappellari;Michael, Scriney;Andrew, McCarren

Description

This dataset enables practitioners to evaluate their time series prediction algorithms on various types of time series

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.7

FAIR Score

77%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

74%

Source

Open Alex

Keywords

DiversityTime seriesForecastingDiverse time seriesTime series generationSynthetic dataSynthetic time seriesTime series prediction performance evaluation

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00