if self.predict_vector is None or self.actual_vector is None:
raise pycmVectorError(VECTOR_ONLY_ERROR)
classes = set.union(set(self.predict_vector), set(self.actual_vector))
if self.positions is None:
positions = {self.label_map[_class] : {"TP":[], "FP":[], "TN":[], "FN":[]} for _class in classes}
predict_vector = self.predict_vector
actual_vector = self.actual_vector
After Change
if self.predict_vector is None or self.actual_vector is None:
raise pycmVectorError(VECTOR_ONLY_ERROR)
if self.positions is None:
classes = list(self.label_map.keys())
positions = {self.label_map[_class] : {"TP":[], "FP":[], "TN":[], "FN":[]} for _class in classes}
[actual_vector, predict_vector] = vector_filter(self.actual_vector, self.predict_vector)
for index, observation in enumerate(predict_vector):
for _class in classes:
