Agent skill · research science · aiskillstore
aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Why this skill is useful
Provides specialized algorithms for time series analysis that the AI wouldn't reliably generate on its own.
What it needs
Requires aeon installed locally. About 5k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Aeon Time Series Machine Learning Overview Aeon is a scikit-learn compatible Python toolkit for time series machine learning. It provides state-of-the-art algorithms for classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. When to Use This Skill Apply this skill when: Classifying or predicting from time series data Detecting anomalies or change points in temporal sequences Clustering similar time series patterns Forecasting future values Finding repeated patterns (motifs) or unusual subsequences (discords) Comparing time series with specialized distance metrics Extracting features from temporal data Installation Core Capabilities 1. Time Series Classification Categorize time series into predefined classes. See references/classification.md for complete algorithm catalog. Quick Start: Algorithm Selection: Speed + Performance: MiniRocketClassifier, Arsenal Maximum Accuracy: HIVECOTEV2, InceptionTimeClassifier Interpretability: ShapeletTransformClassifier, Catch22Classifier Small Datasets: KNeighborsTimeSeriesClassifier with DTW distance 2. Time Series Regression Predict continuous values from time series. See references/regression.md for algorithms. Quick Start: 3. Time Series Clustering Group similar time series without labels. See references/clustering.md for methods. Quick Start: 4. Forecasting Predict future time series values. See references/forecasting.md for forecasters. Quick Start: 5. Anomaly Detection Identify unusual patterns or outliers. See references/anomalydetection.md for detectors. Quick Start: 6. Segmentation Partition time series into regions with change points. See references/segmentation.md. Quick Start: 7. Similarity Search Find similar patterns within or across time series. See references/similaritysearch.md. Quick Start: Feature Extraction and Transformations Transform time series for feature engineering. See references/transformations.md. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/aeon--f3d3c6