30 lines
943 B
Python
30 lines
943 B
Python
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import numpy as np
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import matplotlib.pyplot as plt
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# Parameters
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num_points = 1000 # Number of data points
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radius = 5 # Radius to separate the classes
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# Generate random (x, y) coordinates
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x = np.random.uniform(-10, 10, num_points)
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y = np.random.uniform(-10, 10, num_points)
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# Calculate distance from the origin
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distance = np.sqrt(x**2 + y**2)
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# Class labels: 0 for inside the radius, 1 for outside the radius
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labels = (distance > radius).astype(int)
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# Plot the dataset
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plt.figure(figsize=(8, 8))
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plt.scatter(x[labels == 0], y[labels == 0], color='blue', label='Class 0 (Inside radius)')
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plt.scatter(x[labels == 1], y[labels == 1], color='red', label='Class 1 (Outside radius)')
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plt.axhline(0, color='black',linewidth=0.5)
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plt.axvline(0, color='black',linewidth=0.5)
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plt.grid(color = 'gray', linestyle = '--', linewidth = 0.5)
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plt.xlabel('X')
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plt.ylabel('Y')
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plt.title('Generated Dataset for Classification Task')
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plt.legend()
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plt.show()
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