data-mining
Extract patterns and insights from large datasets using association rules, clustering, classification, and anomaly detection. Use for market basket analysis, customer segmentation, fraud detection, pattern discovery, predictive modeling, and knowledge extraction from structured and unstructured data.
npx skills add majiayu000/claude-skill-registry --skill data-mining --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Data Mining Extract valuable patterns, relationships, and insights from large datasets using computational algorithms. ## Overview Data mining is the process of discovering patterns, correlations, and anomalies within large datasets to predict outcomes and extract actionable knowledge. It combines techniques from statistics, machine learning, and database systems to analyze data from multiple perspectives. This skill covers association rule learning, clustering algorithms, classification methods, and anomaly detection techniques. ## Core Data Mining Techniques | Technique | Purpose | Common Algorithms | Use Cases | |-----------|---------|-------------------|-----------| | Association Rules | Find relationships between items | Apriori, FP-Growth, ECLAT | Market basket analysis, recommendation systems | | Clustering | Group similar items | K-Means, DBSCAN, Hierarchical | Customer segmentation, image segmentation | | Classification | Predict categorical outcomes | Decision Trees, Random Forest, SVM | Spam detection, credit scoring | | Regression | Predict numerical outcomes | Linear Regression, Gradient Boosting | Sales forecasting, price prediction | | Anomaly Detection | Identify
- Overview
- Core Data Mining Techniques
- Association Rule Learning
- Key Concepts
- Apriori Algorithm
- FP-Growth Algorithm
- Applications
- Clustering Algorithms
- K-Means Clustering
- DBSCAN (Density-Based Spatial Clustering)
- Hierarchical Clustering
- Classification Techniques
- Decision Trees
- Random Forest
What does the data-mining skill do?
Extract patterns and insights from large datasets using association rules, clustering, classification, and anomaly detection. Use for market basket analysis, customer segmentation, fraud detection, pattern discovery, predictive modeling, and knowledge extraction from structured and unstructured data.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill data-mining --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.