aeon
Category: data-science-and-ml · License: BSD-3-Clause license · Version: 1.1
Tags: time series, classification, forecasting, anomaly detection, machine learning
When to use it
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.Example requests
Ask your agent in plain language, for example:- “How do I train a fast classifier on my accelerometer windows? Shape is (500, 3, 128).”
- “I have ECG recordings in ecg_train.csv, with 1 row per beat, 140 columns for the samples and a final column for the label (normal or abnormal). I tried sklearn’s RandomForest on the raw values and got about 70% accuracy. I’d like to try elastic-distance methods, and I got
ImportError: cannot import name 'ROCKETClassifier' from 'aeon.classification.convolution_based'. Can you fix the import and compare 1-NN with DTW against a ROCKET-family model, using cross-validation?” - “I have a year of minute-level vibration readings from a turbine. I need to flag the odd stretches and also work out where the machine switched operating regimes. There are no labels. What approach would you take?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole data-science-and-ml category with /plugin install data-science-and-ml@research-agent-skills.