Aeon Time Series Machine Learning

소개

Aeon is a comprehensive Python toolkit designed for time series machine learning, offering state-of-the-art algorithms that integrate seamlessly with scikit-learn. It addresses specialized temporal data challenges such as classification, regression, clustering, and similarity search, making it indispensable for tasks involving sequential patterns or time-indexed observations. Whether you're forecasting future values, detecting anomalies in data streams, or extracting complex features like ROCKET or Catch22, Aeon provides the high-performance tools and deep learning architectures needed to analyze temporal data effectively.

주요 기능

• Comprehensive library of temporal distance metrics like DTW and MSM
• Advanced forecasting, anomaly detection, and segmentation capabilities
• Deep learning architectures specifically designed for temporal sequences
• 2 GitHub stars
• Specialized algorithms for time series classification and regression
• Feature extraction transformers including ROCKET and Catch22

사용 사례

• Classifying sequential patterns into predefined categories with high accuracy
• Predicting future values and trends in time-indexed datasets
• Identifying anomalies or motifs in industrial or physiological sensor data