input: Write a function to create a machine learning algorithm in Python that categorizes a dataset of records into predefined labels based on their features using a Support Vector Classifier (SVC). The function should take the dataset as input, extract the features and labels, train the SVC model, and then predict the label for a given set of features. The function should return the predicted label for the given features.
  assert categorize_records([
   {"label": "apple", "features": [1, 1, 0]}, 
   {"label": "banana", "features": [0, 1, 1]}, 
   {"label": "lemon", "features": [0, 0, 1]}, 
   {"label": "orange", "features": [1, 0, 0]}, 
   {"label": "pear", "features": [0, 1, 0]}, 
  ], [1, 0, 1]) == "banana"
  assert categorize_records([
   {"label": "apple", "features": [1, 1, 0]}, 
   {"label": "banana", "features": [0, 1, 1]}, 
   {"label": "lemon", "features": [0, 0, 1]}, 
   {"label": "orange", "features": [1, 0, 0]}, 
   {"label": "pear", "features": [0, 1, 0]}, 
  ], [1, 1, 0]) == "apple"
  assert categorize_records([
   {"label": "apple", "features": [1, 1, 0]}, 
   {"label": "banana", "features": [0, 1, 1]}, 
   {"label": "lemon", "features": [0, 0, 1]}, 
   {"label": "orange", "features": [1, 0, 0]}, 
   {"label": "pear", "features": [0, 1, 0]}, 
  ], [0, 0, 1]) == "lemon"
  assert categorize_records([
   {"label": "apple", "features": [1, 1, 0]}, 
   {"label": "banana", "features": [0, 1, 1]}, 
   {"label": "lemon", "features": [0, 0, 1]}, 
   {"label": "orange", "features": [1, 0, 0]}, 
   {"label": "pear", "features": [0, 1, 0]}, 
  ], [1, 0, 0]) == "orange"
  assert categorize_records([
   {"label": "apple", "features": [1, 1, 0]}, 
   {"label": "banana", "features": [0, 1, 1]}, 
   {"label": "lemon", "features": [0, 0, 1]}, 
   {"label": "orange", "features": [1, 0, 0]}, 
   {"label": "pear", "features": [0, 1, 0]}, 
  ], [0, 1, 0]) == "pear"
output: def categorize_records(dataset, features):
      from sklearn.svm import SVC
      import numpy as np
      
      X = np.array([record['features'] for record in dataset])
      y = np.array([record['label'] for record in dataset])
      
      svc = SVC(kernel='linear')
      svc.fit(X, y)
      
      return svc.predict([features])[0]