| """Train and persist the house prices regression model and artifacts.""" |
|
|
| from __future__ import annotations |
|
|
| import sys |
| import json |
| from pathlib import Path |
|
|
| import pandas as pd |
| from sklearn.model_selection import train_test_split |
|
|
| PROJECT_ROOT = Path(__file__).resolve().parents[1] |
| sys.path.insert(0, str(PROJECT_ROOT / "src")) |
|
|
| from house_prices.config import ( |
| DATA_CLEAN_PATH, |
| DATA_PROCESSED_DIR, |
| DATA_RAW_PATH, |
| MODEL_DIR, |
| REPORTS_DIR, |
| ) |
| from house_prices.features import build_training_frame |
| from house_prices.modeling import evaluate_model, save_metrics, save_model, train_model |
|
|
|
|
| def _load_source_dataframe() -> pd.DataFrame: |
| if DATA_CLEAN_PATH.exists(): |
| return pd.read_parquet(DATA_CLEAN_PATH) |
| return pd.read_csv(DATA_RAW_PATH) |
|
|
|
|
| def main() -> None: |
| df = _load_source_dataframe() |
| features, target = build_training_frame(df) |
|
|
| x_train, x_test, y_train, y_test = train_test_split( |
| features, |
| target, |
| test_size=0.2, |
| random_state=42, |
| ) |
|
|
| model = train_model(x_train=x_train, y_train=y_train, random_state=42) |
| metrics, y_hat = evaluate_model(model=model, x_test=x_test, y_test=y_test) |
|
|
| DATA_PROCESSED_DIR.mkdir(parents=True, exist_ok=True) |
| x_train.to_parquet(DATA_PROCESSED_DIR / "x_train.parquet", index=False) |
| x_test.to_parquet(DATA_PROCESSED_DIR / "x_test.parquet", index=False) |
| y_train.to_frame(name="target").to_parquet(DATA_PROCESSED_DIR / "y_train.parquet", index=False) |
| y_test.to_frame(name="target").to_parquet(DATA_PROCESSED_DIR / "y_test.parquet", index=False) |
| y_hat.to_frame(name="prediction").to_parquet(DATA_PROCESSED_DIR / "yhat.parquet", index=False) |
|
|
| save_model(model=model, path=MODEL_DIR / "model.joblib") |
| save_metrics(metrics=metrics, path=REPORTS_DIR / "metrics.json") |
| (MODEL_DIR / "feature_order.json").write_text( |
| json.dumps(list(x_train.columns), indent=2), |
| encoding="utf-8", |
| ) |
|
|
| print("Training finished successfully.") |
| print(f"Saved model to: {MODEL_DIR / 'model.joblib'}") |
| print(f"Saved metrics to: {REPORTS_DIR / 'metrics.json'}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
