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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _get_fbeta_score(true_positives, selected, relevant, beta=1):
 """Compute Fbeta score. Args: true_positives: Number of true positive ngrams. selected: Number of selected ngrams. relevant: Number of relevant ngrams. beta: 0 gives precision only, 1 gives F1 score, and Inf gives recall only. Returns: Fbeta score. """

  precision = 1
  if selected > 0:
    precision = true_positives / selected
  if beta == 0:
    return precision
  recall = 1
  if relevant > 0:
    recall = true_positives / relevant
  if precision > 0 and recall > 0:
    beta2 = beta * beta
    return (1 + beta2) * precision * recall / (beta2 * precision + recall)
  else:
    return 0