sklearn-model-trainer
Scikit-learn model training skill with cross-validation, hyperparameter tuning, pipeline construction, and model serialization. Enables automated ML model development using scikit-learn's comprehensive toolkit.
npx skills add a5c-ai/babysitter --skill sklearn-model-trainer --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.
# Scikit-learn Model Trainer Train machine learning models using scikit-learn with cross-validation, hyperparameter tuning, and pipeline construction. ## Overview This skill provides comprehensive capabilities for training machine learning models using scikit-learn. It supports the full model development workflow from data preprocessing through model training, evaluation, and serialization. ## Capabilities ### Model Training - Train classification models (LogisticRegression, RandomForest, SVM, etc.) - Train regression models (LinearRegression, GradientBoosting, etc.) - Train clustering models (KMeans, DBSCAN, etc.) - Support for ensemble methods (VotingClassifier, Stacking, etc.) ### Cross-Validation - K-fold cross-validation - Stratified K-fold for imbalanced datasets - Time series split for temporal data - Leave-one-out and leave-p-out validation - Custom cross-validation strategies ### Hyperparameter Tuning - GridSearchCV for exhaustive search - RandomizedSearchCV for random sampling - Halving search strategies for efficiency - Custom scoring functions - Multi-metric evaluation ### Pipeline Construction - Feature preprocessing pipelines - Column transformers for heterogeneous da
- Overview
- Capabilities
- Model Training
- Cross-Validation
- Hyperparameter Tuning
- Pipeline Construction
- Model Serialization
- Prerequisites
- Installation
- Optional Dependencies
- Usage Patterns
- Basic Model Training
- Pipeline with Preprocessing
- Hyperparameter Tuning with GridSearchCV
pip install scikit-learn>=1.0.0 joblib pandas numpy For ONNX export pip install skl2onnx onnxruntime For additional preprocessing pip install category_encoders imbalanced-learn
What does the sklearn-model-trainer skill do?
Scikit-learn model training skill with cross-validation, hyperparameter tuning, pipeline construction, and model serialization. Enables automated ML model development using scikit-learn's comprehensive toolkit.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill sklearn-model-trainer --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 a5c-ai/babysitter, a repository with 1,642 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.