File size: 2,201 Bytes
e1c0f4a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | """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 ( # noqa: E402
DATA_CLEAN_PATH,
DATA_PROCESSED_DIR,
DATA_RAW_PATH,
MODEL_DIR,
REPORTS_DIR,
)
from house_prices.features import build_training_frame # noqa: E402
from house_prices.modeling import evaluate_model, save_metrics, save_model, train_model # noqa: E402
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()
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