categorical-encoder
Эксперт categorical encoding. Используй для ML feature engineering, one-hot, target encoding и embeddings.
npx skills add majiayu000/claude-skill-registry --skill categorical-encoder --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.
# Categorical Encoder Expert Эксперт по кодированию категориальных переменных для машинного обучения. ## Выбор на основе кардинальности | Кардинальность | Рекомендация | |----------------|--------------| | Низкая (<10) | One-hot, Dummy | | Средняя (10-50) | Target, Frequency, Binary | | Высокая (>50) | Hash, Embeddings | | Порядковая | Ordinal | ## One-Hot Encoding ```python from sklearn.preprocessing import OneHotEncoder import pandas as pd # Для pandas df_encoded = pd.get_dummies(df, columns=['category_col'], prefix='cat') # Для sklearn encoder = OneHotEncoder(sparse_output=False, handle_unknown='ignore') X_train_encoded = encoder.fit_transform(X_train[['category_col']]) X_test_encoded = encoder.transform(X_test[['category_col']]) # Получить названия признаков feature_names = encoder.get_feature_names_out(['category_col']) ``` ## Target Encoding с кросс-валидацией ```python from sklearn.model_selection import KFold import numpy as np def target_encode_cv(X, y, column, n_splits=5, alpha=1.0): """ Target кодирование с CV для предотвращения переобучения """ kf = KFold(n_splits=n_splits, shuffle=True, random_state=42) encoded = np.zeros(len(X)) global_mean = y.mean() for train_idx, v
- Выбор на основе кардинальности
- One-Hot Encoding
- Target Encoding с кросс-валидацией
- Binary Encoding
- Frequency и Count Encoding
- Embeddings для высокой кардинальности
- Multiple Encoding Strategy
- Production-ready Encoder
- Рекомендации для моделей
- Предотвращение утечки данных
- Валидация
- Лучшие практики
What does the categorical-encoder skill do?
Эксперт categorical encoding. Используй для ML feature engineering, one-hot, target encoding и embeddings.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill categorical-encoder --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.