Perform time series classification, forecasting, and anomaly detection with scikit-learn compatible APIs.
npx skills add https://github.com/yf8578/clawomics --skill aeon-yf8578
Please help me install this Agent Skill. Skill: aeon Source: https://github.com/yf8578/clawomics/tree/main/skills/aeon Command: npx skills add https://github.com/yf8578/clawomics --skill aeon-yf8578
This Skill empowers users to perform advanced time series analysis, including classification, regression, forecasting, and anomaly detection, by leveraging a comprehensive suite of state-of-the-art algorithms.
Use the aeon skill to classify the time series data in 'sensor_readings.ts' using the MiniRocketClassifier.
High-intent search queries and answers about installing and using this skill.
Time series forecasting predicts future values using models like ARIMA, ETS, or Temporal Convolutional Networks. This Skill applies these algorithms to historical data trends to project future sequences for univariate or multivariate datasets.
Anomaly detection in multivariate time series identifies unusual patterns using algorithms like STOMP or COPOD. This toolkit processes temporal data to pinpoint deviations, useful for applications like industrial sensor monitoring and equipment failure prediction.
Classifying temporal data is supported via scikit-learn compatible APIs. You can categorize time series using methods like ROCKET, HIVECOTEV2, or deep learning networks, allowing integration into standard machine learning pipelines.
Univariate and multivariate time series analysis are fully supported. The toolkit handles various machine learning tasks including classification, regression, clustering, segmentation, and similarity search across both data types.
Using the MiniRocketClassifier involves loading your time series file, such as 'sensor_readings.ts', and passing it to the classifier. This applies the ROCKET algorithm to categorize the temporal sensor data efficiently.
Time series clustering and similarity search utilize state-of-the-art algorithms to group temporal data and find matching sequences. This toolkit provides these functions alongside segmentation and classification for comprehensive temporal analysis.
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