import numpy as np
import matplotlib.pyplot as plt
from sklearn.svm import SVR

# House size (in square feet)
X = np.array([500, 800, 1000, 1200, 1500, 1800, 2000]).reshape(-1, 1)

# Corresponding house prices (in thousands)
y = np.array([50, 80, 100, 120, 150, 180, 200])

model = SVR(kernel='rbf', epsilon=10)
model.fit(X, y)

predicted_price = model.predict([[1600]])
print("Predicted house price:", predicted_price[0])

plt.scatter(X, y, label="Actual Data")
plt.plot(X, model.predict(X), label="SVR Prediction Curve")
plt.xlabel("House Size (sq ft)")
plt.ylabel("House Price")
plt.legend()
plt.show()

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