def distributionForInstance(self, instance: Instance, useLaplace: bool):
numbers = []
for i in range(instance.numClasses()):
if not useLaplace:
numbers.append(self.getProbs(i, instance, 1))
else:
numbers.append(self.getProbsLaplace(i, instance, 1))
return numbers
def distributionForInstance(self,instance:Instance)->List[float]:
dist=[0]*instance.numClasses()
if instance.classAttribute().type() == Attribute.NOMINAL:
classification=self.classifyInstance(instance)
if Utils.isMissingValue(classification):
return dist
else:
dist[int(classification)]=1.0
return dist
elif instance.classAttribute().type() == Attribute.NUMERIC or instance.classAttribute().type() == Attribute.DATE:
dist[0]=self.classifyInstance(instance)
return dist
return dist