sklearn文档中类似于数组的形状（n_samples，）vs [n_samples]

1 回答

• 0

  您可以使用一个简单的示例来测试它：

  import numpy as np
  from sklearn.naive_bayes import GaussianNB
  
  #create some data
  X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
  Y = np.array([1, 1, 1, 2, 2, 2])
  
  #create the model and fit it
  clf = GaussianNB()
  clf.fit(X, Y)
  
  #check the type of some attributes
  type(clf.class_prior_)
  type(clf.class_count_)
  
  #check the shapes of these attributes
  clf.class_prior_.shape
  clf.class_count_
  

  Or more advanced searching:

  #verify that it is a numpy nd array and NOT a list
  isinstance(clf.class_prior_, np.ndarray)
  isinstance(clf.class_prior_, list)
  

  同样，您可以检查所有属性 .

  Results

  numpy.ndarray
  
  numpy.ndarray
  
  (2,)
  
  array([ 3.,  3.])
  
  True
  
  False
  

  结果表明这些属性是 numpy nd arrays .

  回复于 2024-05-19T16:11:55+08:00