input: Write a python function to predict class using LogisticRegression model.
  assert predict_class([1, 2, 3, 4])==[0]
  assert predict_class([5, 6, 7, 8])==[1]
  assert predict_class([9, 10, 11, 12])==[0]
output: def predict_class(input_data):
      from sklearn.linear_model import LogisticRegression
      import numpy as np
  
      # Sample data
      X_train = np.array([[1, 2, 3, 4],
                          [5, 6, 7, 8],
                          [9, 10, 11, 12]])
      y_train = np.array([0, 1, 0])
  
      # Create logistic regression model
      model = LogisticRegression()
      
      # Fit the model
      model.fit(X_train, y_train)
      
      # Predict class for input data
      prediction = model.predict([input_data])
      
      return prediction.tolist()