aeon

Topics in the source

• Aeon Time Series Machine Learning
• Overview
• When to Use This Skill
• Installation
• Core Capabilities
• 1. Time Series Classification
• 2. Time Series Regression
• 3. Time Series Clustering

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. 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 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 Predict continuous values from time series. See references/regression.md for algorithms. Quick Start: Group similar time series without labels. See references/clustering.md for methods. Quick Start: Predict future time se

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