classification-helper
Quick classifier training with automatic model selection, hyperparameter tuning, and comprehensive evaluation metrics.
Resources
1Install
npx skillscat add dkyazzentwatwa/chatgpt-skills/classification-helper Install via the SkillsCat registry.
We need to produce a 2-3 sentence plain-text summary, objective, factual, no marketing language, no superlatives, no calls to action, natural prose, no bullet points, no headings, no markdown. At most 60 words. Must be only the summary text, no quotes. Provide only the summary. We need to describe what the skill does: quick classifier training with automatic model selection, hyperparameter tuning, comprehensive evaluation metrics. Problem it solves: simplifies training classification models, automates selection and evaluation.
Classification Helper
Train and evaluate classification models with automatic model selection.
Features
- Auto Model Selection: Compare multiple classifiers
- Hyperparameter Tuning: Grid/random search
- Evaluation Metrics: Accuracy, precision, recall, F1, ROC-AUC
- Cross-Validation: K-fold validation
- Confusion Matrix: Detailed error analysis
- Feature Importance: Top predictive features
- Model Export: Save trained models
CLI Usage
python classification_helper.py --data train.csv --target class --test test.csv --output model.pklDependencies
- scikit-learn>=1.3.0
- pandas>=2.0.0
- numpy>=1.24.0
- matplotlib>=3.7.0
- seaborn>=0.12.0
Categories
Install
npx skillscat add dkyazzentwatwa/chatgpt-skills/classification-helper Install via the SkillsCat registry.