hiring_assessment/backend/app/services/house_price_predictor.py

17 lines
558 B
Python

import os
import joblib
import numpy as np
from backend.app.dtos.house.house_features import HouseFeatures
class HousePricePredictor:
"""
Mock ML model that predicts house prices.
In a real scenario, this would load a trained model.
"""
def __init__(self):
self.model = joblib.load("backend/app/ai_models/price_predictor.pkl")
def predict(self, features: HouseFeatures) -> float:
X = np.array([[features.square_feet, features.bedrooms, features.bathrooms]])
return self.model.predict(X)[0] * 100000