Text Analyzer
CommunityML-enabled text analysis for trading signals.
AuthorIgorGanapolsky
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill extracts numerical features from financial text (news, earnings reports, social media) to feed ML-based trading decisions, enabling more informed decisions with less manual effort.
Core Features & Use Cases
- BoW features: word frequency metrics for quick baseline signals.
- TF-IDF features: keyword importance to capture meaningful terms.
- Embeddings: FinBERT-based 768-dim vectors for semantic context.
- Sentiment scoring: domain-specific score to gauge market mood.
- Batch analysis: analyze multiple texts (headlines, articles, posts) to generate trading signals.
Quick Start
Run the Text Analyzer on a sample piece of financial text to produce a feature vector and sentiment signals, then feed it into your ML model.
Dependency Matrix
Required Modules
src/ml/text_feature_engineering.py
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Text Analyzer Download link: https://github.com/IgorGanapolsky/trading/archive/main.zip#text-analyzer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.