code: def test_univariate_svd():
      w_exp = np.array([[9.1]])
      b_exp = np.array([-34.7])
      svd_lr = LinearRegression(method="svd")
      svd_lr.fit(X_rm, y)
      assert_almost_equal(svd_lr.w_, w_exp, decimal=1)
      assert_almost_equal(svd_lr.b_, b_exp, decimal=1)
  
imports: import numpy
  from numpy.testing import assert_almost_equal
  from sklearn.base import clone
  from mlxtend.data import boston_housing_data
  from mlxtend.regressor import LinearRegression
label_desc: Use image node_id 5 for calling a global function with example usage: test_univariate_svd() without return types