code: def test_dtype_of_classifier_probas(strategy):
      y = [0, 2, 1, 1]
      X = np.zeros(4)
      model = DummyClassifier(
          strategy=strategy, random_state=0, constant=0
      )
      probas = model.fit(X, y).predict_proba(X)
  
      assert probas.dtype == np.float64
  
imports: import numpy
  import pytest
  import scipy.sparse
  from sklearn.base import clone
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS
  from sklearn.utils.stats import _weighted_percentile
label_desc: Use image node_id 43 for calling a global function with example usage: test_dtype_of_classifier_probas(strategy) without return types