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Found 4 papers, 1 papers with code
Convolutional and Deep Learning based techniques for Time Series Ordinal Classification
Hence, this paper presents a first benchmarking of TSOC methodologies, exploiting the ordering of the target labels to boost the performance of current TSC state-of-the-art.
A Dictionary-based approach to Time Series Ordinal Classification
Time Series Classification (TSC) is an extensively researched field from which a broad range of real-world problems can be addressed obtaining excellent results.
Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression
FreshPRINCE is a pipeline estimator consisting of a transform into a wide range of summary features followed by a rotation forest regressor.
Time series clustering based on the characterisation of segment typologies
These clusters are used to represent all time series in the same dimensional space, after defining another specific mapping process.
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