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Bake off redux: a review and experimental evaluation of recent time series classification algorithms
In 2017, a research paper (Bagnall et al. Data Mining and Knowledge Discovery 31 (3): 606-
660.) compared 18 Time Series Classification (TSC) algorithms on 85 datasets from the …
660.) compared 18 Time Series Classification (TSC) algorithms on 85 datasets from the …
Deep learning for time series classification and extrinsic regression: A current survey
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
learning tasks. Deep learning has revolutionized natural language processing and computer …
aeon: a Python toolkit for learning from time series
Abstract aeon is a unified Python 3 library for all machine learning tasks involving time
series. The package contains modules for time series forecasting, classification, extrinsic …
series. The package contains modules for time series forecasting, classification, extrinsic …
An approach to multiple comparison benchmark evaluations that is stable under manipulation of the comparate set
The measurement of progress using benchmarks evaluations is ubiquitous in computer
science and machine learning. However, common approaches to analyzing and presenting …
science and machine learning. However, common approaches to analyzing and presenting …
Lite: Light inception with boosting techniques for time series classification
Deep learning models have been shown to be a powerful solution for Time Series
Classification (TSC). State-of-the-art architectures, while conducting promising results on the …
Classification (TSC). State-of-the-art architectures, while conducting promising results on the …
A hands-on introduction to time series classification and regression
Time series classification and regression are rapidly evolving fields that find areas of
application in all domains of machine learning and data science. This hands on tutorial will …
application in all domains of machine learning and data science. This hands on tutorial will …
Look into the lite in deep learning for time series classification
Deep learning models have been shown to be a powerful solution for Time Series
Classification (TSC). State-of-the-art architectures, while producing promising results on the …
Classification (TSC). State-of-the-art architectures, while producing promising results on the …
Convolutional-and Deep Learning-Based Techniques for Time Series Ordinal Classification
Time-series classification (TSC) covers the supervised learning problem where input data is
provided in the form of series of values observed through repeated measurements over time …
provided in the form of series of values observed through repeated measurements over time …
Finding foundation models for time series classification with a pretext task
Over the past decade, Time Series Classification (TSC) has gained an increasing attention.
While various methods were explored, deep learning–particularly through Convolutional …
While various methods were explored, deep learning–particularly through Convolutional …
Towards data-driven quality monitoring for advanced metal inert gas welding processes in body-in-white
In recent years, numerous monitoring approaches have been developed in the field of
intelligent welding manufacturing to predict quality-related characteristics using process …
intelligent welding manufacturing to predict quality-related characteristics using process …