input: def classify_string(input_string: str) -> str:
      """ Create a machine learning classifier in Python for categorizing user input.
      >>> classify_string("Hello, how are you today?")
      'Greeting'
      >>> classify_string("What is the weather like tomorrow?")
      'Weather'
      """
output:     import re
      from sklearn.feature_extraction.text import TfidfVectorizer
      from sklearn.naive_bayes import MultinomialNB
      from sklearn.pipeline import make_pipeline
  
      # Sample training data
      data = [
          ("Hello, how are you today?", "Greeting"),
          ("What is the weather like tomorrow?", "Weather"),
          ("Good morning!", "Greeting"),
          ("Is it going to rain?", "Weather"),
          ("How's your day?", "Greeting"),
          ("Will it be sunny?", "Weather"),
      ]
  
      # Split data into features and labels
      texts, labels = zip(*data)
  
      # Create a pipeline with TF-IDF vectorizer and Naive Bayes classifier
      model = make_pipeline(TfidfVectorizer(), MultinomialNB())
  
      # Train the model
      model.fit(texts, labels)
  
      # Predict the category of the input string
      return model.predict([input_string])[0]