package?weka.classifiers.xy;

import?weka.classifiers.Classifier;
import?weka.core.Instance;
import?weka.core.Instances;
import?weka.core.Utils;

public?class?LWNB?extends?Classifier{
	int?K=30;
????public?String[]?getOptions（）?{
????	String?[]?options?=?new?String?[1];
????	options[0]=“K-number“;
????	return?options;
????}
????	public?int?getNumber（）{
????		return?K;
????	}
????	public?void?setNumber（int?number）{
????		K=number;
????	}
	
	Instances?train_set;
	private?int?m_NumClasses;
	private?int?m_numInstances;
	private?int?m_numAttribute;
	
	public?void?buildClassifier（Instances?instances）?throws?Exception?{
		train_set=new?Instances（instances）;
		m_NumClasses=instances.numClasses（）;
		m_numInstances=instances.numInstances（）;
		m_numAttribute=instances.numAttributes（）;
	}
	
	public?double?[]?distributionForInstance（Instance?instance）throws?Exception?{
		double?weight[]=new?double[K];
		double[]distances=calculateDistance（instancetrain_set）;
		double?temp=0;
		for（int?i=0;i			for（int?j=i+1;j				if（distances[i]>distances[j]）{
					temp=distances[i];
					distances[i]=distances[j];
					distances[j]=temp;
					train_set.swap（i?j）;
				}
			}
		}
		Instances?newinstances=new?Instances（train_set0）;
		for（int?i=0;i			newinstances.add（train_set.instance（i））;
		}
		double?total_weight=0;
		for（int?i=0;i			distances[i]/=distances[K-1];
			distances[i]=1-distances[i];
			total_weight+=distances[i];
		}
		for（int?i=0;i			weight[i]=（distances[i]*K）/total_weight;
		}
		m_numInstances=newinstances.numInstances（）;
		m_NumClasses=newinstances.numClasses（）;
		double?[]?probs=new?double[m_NumClasses];//p（c|a）
		double?prob_c[]=new?double[m_NumClasses];//p（c）
		for（int?i=0;i			double?t_same=0;
			double?t_weight=0;
			for（int?j=0;j				if（（int）newinstances.instance（j）.classValue（）==i）{
					t_same+=weight[j];
				}
				t_weight+=weight[j];
			}
			prob_c[i]=（（1+t_same）/（m_NumClasses+t_weight））;
		}
//		for（int?i=0;i//			prob_c[i]/=m_NumClasses;
//		}
		double[][]class_attri=new?double[m_numAttribute-1][m_NumClasses];//p（a|c）
		for（int?i=0;i			int?num_attri=newinstances.attribute（i）.numValues（）;
			double?t_same=0;
			double?t_weight=0;
			for（int?j=0;j				for（int?k=0;k					if（（int）instance.value（i）==（int）newinstances.instance（k）.value（i）&&（int）newinstances.instance（k）.classValue（）==j）{
						t_same+=weight[k];
					}
					if（（int）newinstances.instance（k）.classValue（）==j）{
						t_weight+=weight[k];
					}
				}
				class