3260 papers • 126 benchmarks • 313 datasets
The episode classification is a branch of the classification aiming to classify groups of observations of a Time Series. (Example: critical episodes/ normal episode)
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These leaderboards are used to track progress in episode-classification-11
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Use these libraries to find episode-classification-11 models and implementations
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Compared to systems using Extreme Gradient Boosting, Support Vector Classification or Naive Bayes as a predictive model, the proposed system was found to be highly dominant and confirmed its superiority over the Layered Learning approach.
Adding a benchmark result helps the community track progress.