# genpark-tfidf-vectorizer-cosine-similarity-skill

> genpark-tfidf-vectorizer-cosine-similarity-skill — alpha-park-genpark-tfidf-vectorizer-cosine-similarity-skill. Use this tool when you need to analyze and compare text data based on semantic similarity, as it generates TF-IDF vectors with sublinear scaling and smooth IDFs, and calculates pairwise cosine similarity between them. This skill solves problems in text classification, information retrieval, and topic modeling by providing a quantitative measure of text similarity. It takes text data as input and outputs cosine similarity scores, making it suitable for applications such as document clustering, duplicate detection, and recommendation systems.

Canonical page: https://skillsregistry.net/skills/alpha-park-genpark-tfidf-vectorizer-cosine-similarity-skill  
JSON: https://api.skillsregistry.net/v1/skills/alpha-park-genpark-tfidf-vectorizer-cosine-similarity-skill

## Description

TF-IDF sublinear vectorizer with smooth inverse document frequency and pairwise cosine similarity.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Alpha-Park/genpark-tfidf-vectorizer-cosine-similarity-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alpha-park-genpark-tfidf-vectorizer-cosine-similarity-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-tfidf-vectorizer-cosine-similarity-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alpha-park-genpark-tfidf-vectorizer-cosine-similarity-skill/pull`

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