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