input: Write a function to create a machine learning model in Python that predicts customer lifetime value given a customer's past transactions. The function should preprocess the data, train the model using a RandomForestRegressor, and make predictions on new customer data.
  assert predict_ltv([[10,100,5,3]], model, scaler) == 4502.3
  assert predict_ltv([[5,50,2,1]], model, scaler) == 2301.5
  assert predict_ltv([[20,200,10,6]], model, scaler) == 5600.7
  assert predict_ltv([[15,150,7,4]], model, scaler) == 3802.1
  assert predict_ltv([[30,300,15,9]], model, scaler) == 6704.8
output: def predict_ltv(new_data, model, scaler):
      new_data = scaler.transform(new_data)
      predictions = model.predict(new_data)
      return predictions[0]