A common task for time series machine learning is **classification. **Given a set of time series with class labels, can we train a model to accurately predict the class of new time series?

Source: Univariate time series classification with sktime

_There are many algorithms dedicated to time series classification! _This means you don’t have wrangle your data into a scikit-learn classifier or to turn to deep learning to solve every time series classification task.

In this article, I will introduce five categories of time series classification algorithms with details of specific algorithms. These specific algorithms have been shown to perform better on average than a baseline classifier (KNN) over a large number of different datasets [1].

1. Distance-based (KNN with dynamic time warping)
2. Interval-based (TimeSeriesForest)
3. Dictionary-based (BOSS, cBOSS)
4. Frequency-based (RISE — like TimeSeriesForest but with other features)
5. Shapelet-based (Shapelet Transform Classifier)

I conclude with brief guidance on selecting an appropriate algorithm.

#machine-learning #time-series-analysis #supervised-learning #data-science #artificial-intelligence