code: def candidate_scores(self) -> numpy.typing.NDArray[numpy.float_]:
      if not self._fitted:
          raise ValueError("Must call fit() before candidate_scores()")
      return self._classifier.predict_proba(self._features)[
          :, 1
      ].reshape(-1, 1)
  
imports: from __future__ import annotations
  import logging
  import random
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, overload
  from warnings import warn
  import numpy
  import numpy.typing
  import sklearn.linear_model
  import dedupe.core
  import dedupe.training
label_desc: Use image node_id 4 for calling the MatchLearner obj's underlying member method code with example usage: obj.candidate_scores() and returns: self