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a guest Jan 18th, 2019 58 Never
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  1. w_true = np.array([2.0,-1.0])
  2. n_objects = 200
  3. n_features = 2
  4. X1 = np.random.uniform(-2,2, (n_objects, 1))
  5. X2 = np.random.normal(1,2, (n_objects, 1))
  6. X = np.hstack((X1, X2))
  7. y = X.dot(w_true) + np.random.normal(0,1, (n_objects))
  8. w_0 = np.random.uniform(-2, 2, (n_features))
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