The model is used to detect if there is any error in the engine of a car with the sound of its engine!
The dataset is a part of the competition which is available in timeseriesclassification
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels.
This model is based on ROCKET
Most methods for time series classification that attain state-of-the-art accuracy have high computational complexity, requiring significant training time even for smaller datasets, and are intractable for larger datasets. Additionally, many existing methods focus on a single type of feature such as shape or frequency. Building on the recent success of convolutional neural networks for time series classification, we show that simple linear classifiers using random convolutional kernels achieve state-of-the-art accuracy with a fraction of the computational expense of existing methods.
Accuracy 94% using RidgeClassifier
(https://github.com/Vikram12301/Time-Series-Classification-for-FordA/tree/main/Models/DL)
Accuracy 97%
1.https://towardsdatascience.com/a-brief-introduction-to-time-series-classification-algorithms-7b4284d31b97 2.https://pub.towardsai.net/rocket-fast-and-accurate-time-series-classification-f54923ad0ac9