code: def _probabilities(self, scores, class_count_):
      probsp2 = np.zeros(
          (class_count_, class_count_), dtype=scores.dtype
      )
  
      index = 0
      for i in range(class_count_):
          for j in range(i + 1, class_count_):
              val1 = sigmoid_probability(
                  scores[index],
                  self._svm.atts.prob_a[index],  # type: ignore
                  self._svm.atts.prob_b[index],  # type: ignore
              )
              val2 = max(val1, 1.0e-7)
              val2 = min(val2, (1 - 1.0e-7))
              probsp2[i, j] = val2
              probsp2[j, i] = 1 - val2
              index += 1
      return multiclass_probability(class_count_, probsp2)
  
file_path: onnx/onnx/reference/ops/aionnxml/op_svm_classifier.py
imports: import numpy
  from onnx.reference.ops.aionnxml._common_classifier import compute_logistic, compute_probit, compute_softmax_zero, logistic, softmax, softmax_zero
  from onnx.reference.ops.aionnxml._op_run_aionnxml import OpRunAiOnnxMl
  from onnx.reference.ops.aionnxml.op_svm_helper import SVMCommon
label_desc: Use image node_id 3 for calling the SVMClassifier obj's underlying member method code with example usage: obj._probabilities(scores, class_count_) and returns: multiclass_probability