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README.md
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@@ -11,3 +11,4 @@ Full credits go to [Theodoros Ntakouris](https://github.com/ntakouris).
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This repository contains the model from [this notebook on time-series classification using the attention mechanism](https://keras.io/examples/timeseries/timeseries_classification_transformer/).
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This repository contains the model from [this notebook on time-series classification using the attention mechanism](https://keras.io/examples/timeseries/timeseries_classification_transformer/).
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The dataset we are using here is called [FordA](http://www.j-wichard.de/publications/FordPaper.pdf). The data comes from the UCR archive. The dataset contains 3601 training instances and another 1320 testing instances. Each timeseries corresponds to a measurement of engine noise captured by a motor sensor. For this task, the goal is to automatically detect the presence of a specific issue with the engine. The problem is a balanced binary classification task.
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