The data is from a Kaggle competition Tabular Playground Series April 2022. The multivariate time series consists of 13 time series, each of which has 60 data points.

This is a binary classification problem, so we need to predict the probability of an input being in group 1.

I tried various approaches, both in the feature extraction and in the modelling stages.

• Feature extraction
  • ROCKET
  • Shapelets
  • None
• Modelling
  • Gradient Boosting
  • Neural Network (the basic, a fully connected layer)
  • LSTM
  • Logistic regression

Three notebooks are included in this repository. The first two notebooks have their own repo, but I also put them here to complete the collection.

1. tps_apr2022_rocket focus on ROCKET as a feature extractor. The video is here
2. shapelet_tslearn focus on Shapelets to transform the dataset. The video is here. Note that I didn't set the seed for learning shapelets, so the shapelets visualizations in this notebook may look a little bit different than what you see in the video. But that doesn't affect the model performance.
3. The video for models with low AUC is here. In that video I also share my opinion about what we can learn from this project.