Which clustering algorithms are supported by this skill?

The skill supports a variety of popular unsupervised learning algorithms, most notably K-means, DBSCAN, and hierarchical clustering.

Can this skill be used for anomaly detection?

Yes, by utilizing the DBSCAN algorithm, the skill can effectively identify outliers and anomalies that do not fit into dense clusters.

How do I see the results of the clustering analysis?

Claude will provide cluster assignments for your data points, key evaluation metrics, and visual artifacts like scatter plots to illustrate the groupings.

Does it handle data preprocessing automatically?

Yes, the skill generates code to handle essential preprocessing steps like feature scaling and normalization to improve algorithm accuracy.

What Python libraries does this skill typically use?

The skill primarily utilizes industry-standard libraries such as scikit-learn for ML, pandas for data handling, and matplotlib or seaborn for visualization.

Clustering Algorithm Runner

Name: Clustering Algorithm Runner
Author: jeremylongshore

byjeremylongshore

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883

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Ciencia de Datos y ML

Executes unsupervised machine learning tasks by applying clustering algorithms like K-means and DBSCAN to analyze data structures and identify groupings.

The Clustering Algorithm Runner skill empowers Claude to act as a data scientist by automating the end-to-end clustering process. It handles data loading, preprocessing (such as scaling and normalization), and the execution of various algorithms including K-means, DBSCAN, and hierarchical clustering. By generating production-grade Python code with scikit-learn, the skill provides not just cluster assignments, but also critical performance metrics like Silhouette scores and insightful visualizations to help users understand the underlying patterns and anomalies within their datasets.

Características Principales

01Generation of performance metrics like Silhouette Score and Davies-Bouldin index

02Support for multiple algorithms including K-means, DBSCAN, and hierarchical clustering

03Built-in error handling and data validation for robust ML execution

04883 GitHub stars

05Automated data preprocessing, scaling, and normalization

06Integrated visualization capabilities for cluster-labeled scatter plots

Casos de Uso

01Segmenting customer databases into distinct personas for targeted marketing

02Detecting anomalies and outliers in network traffic or financial logs

03Exploratory data analysis to discover natural groupings in unlabeled research data

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills clustering-algorithm-runner

For use in Claude.ai and ChatGPT

Características Principales

01Generation of performance metrics like Silhouette Score and Davies-Bouldin index

02Support for multiple algorithms including K-means, DBSCAN, and hierarchical clustering

03Built-in error handling and data validation for robust ML execution

04883 GitHub stars

05Automated data preprocessing, scaling, and normalization

06Integrated visualization capabilities for cluster-labeled scatter plots

Casos de Uso

01Segmenting customer databases into distinct personas for targeted marketing

02Detecting anomalies and outliers in network traffic or financial logs

03Exploratory data analysis to discover natural groupings in unlabeled research data

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills clustering-algorithm-runner

For use in Claude.ai and ChatGPT