35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
import random
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from typing import List, Tuple
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class HousePricePredictor:
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"""
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Mock ML model that predicts house prices.
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In a real scenario, this would load a trained model.
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"""
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def __init__(self):
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# Mock initialization - in reality would load model weights
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pass
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def predict(self, square_feet: float, bedrooms: int, bathrooms: float) -> Tuple[float, float, List[float]]:
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"""
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Mock prediction method that returns:
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- predicted price
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- confidence score
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- similar listing prices
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"""
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# Mock prediction logic
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base_price = square_feet * 200
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bedroom_value = bedrooms * 25000
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bathroom_value = bathrooms * 15000
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predicted_price = base_price + bedroom_value + bathroom_value
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# Add some randomness to make it interesting
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confidence_score = random.uniform(0.8, 0.99)
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similar_listings = [
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predicted_price * random.uniform(0.9, 1.1)
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for _ in range(3)
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]
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return predicted_price, confidence_score, similar_listings |