input: Write a python function to create a decision tree classifier that can predict gender based on age, height, and weight using sklearn.
  assert predict_gender([[24, 185, 85]]) == ['male']
  assert predict_gender([[20, 175, 65]]) == ['female']
  assert predict_gender([[23, 180, 75]]) == ['male']
output: def predict_gender(features):
      from sklearn.tree import DecisionTreeClassifier
      import numpy as np
  
      # Example training data: [age, height, weight]
      X = np.array([
          [25, 180, 80],  # male
          [30, 170, 70],  # female
          [22, 160, 50],  # female
          [28, 175, 75],  # male
          [19, 165, 60],  # female
          [35, 190, 90],  # male
          [23, 150, 45],  # female
          [27, 185, 85]   # male
      ])
      y = np.array(['male', 'female', 'female', 'male', 'female', 'male', 'female', 'male'])
  
      clf = DecisionTreeClassifier()
      clf.fit(X, y)
  
      return clf.predict(features).tolist()