input: Write a python function to predict gender based on height, weight, and shoe size using a decision tree classifier.
  assert predict_gender(6, 170, 9) == 'male'
  assert predict_gender(5.5, 150, 6) == 'female'
  assert predict_gender(5.7, 160, 8) == 'female'
  assert predict_gender(5.9, 180, 10) == 'male'
output: def predict_gender(height, weight, shoe_size):
      from sklearn.tree import DecisionTreeClassifier
      import numpy as np
      
      # Training data: [height, weight, shoe_size]
      X = np.array([
          [6, 180, 12], [5.92, 190, 11], [5.58, 170, 12], [5.92, 165, 10],
          [5, 100, 6], [5.5, 150, 8], [5.42, 130, 7], [5.75, 150, 9]
      ])
      
      # Gender labels: 1 for male, 0 for female
      y = np.array([1, 1, 1, 1, 0, 0, 0, 0])
      
      # Train the decision tree classifier
      clf = DecisionTreeClassifier()
      clf.fit(X, y)
      
      # Predict the gender
      prediction = clf.predict([[height, weight, shoe_size]])[0]
      
      return 'male' if prediction == 1 else 'female'