# Time Series Machine Learning

Handles time series classification, forecasting, anomaly detection and similarity search.

- Repository: https://github.com/K-Dense-AI/scientific-agent-skills (55651 stars)
- Category: Data and ML
- License: BSD-3-Clause license
- Last updated: 2026-10-26
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add K-Dense-AI/scientific-agent-skills --skill aeon -g -a claude-code -y`
Codex: `npx skills add K-Dense-AI/scientific-agent-skills --skill aeon -g -a codex -y`
Cursor: `npx skills add K-Dense-AI/scientific-agent-skills --skill aeon -g -a cursor -y`
Gemini CLI: `npx skills add K-Dense-AI/scientific-agent-skills --skill aeon -g -a gemini-cli -y`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Aeon Time Series Machine Learning

## Overview

Aeon is a scikit-learn compatible Python toolkit for time series machine learning ([aeon-toolkit.org](https://www.aeon-toolkit.org/)). It provides algorithms across classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, distances, transformations, benchmarking, and visualization, with a consistent estimator API.

**Version note:** Reviewed against **aeon 1.6.0** (Python 3.13). Small synthetic checks cover classification, regression, clustering, forecasts, preprocessing, distances, search, segmentation, matrix profiles, metrics, and local dataset I/O. Remote archive and TensorFlow training snippets are illustrative; they were not executed during this review. Reference catalogs are selected methods, not exhaustive lists. See the [1.6 release notes](https://www.aeon-toolkit.org/en/stable/changelogs/v1.6.html).

## 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

Requires **Python 3.11-3.14**. Pin the reviewed release for reproducibility:

```bash
uv pip install "aeon==1.6.0"
```

Install only the extras required by the chosen estimator. The broad optional set is available as:

```bash
uv pip install "aeon[all_extras]==1.6.0"
```

On zsh, quote the extras: `uv pip install "aeon[all_extras]==1.6.0"`.

The rest: https://github.com/K-Dense-AI/scientific-agent-skills/blob/HEAD/skills/aeon/SKILL.md