knn.rar_K._KNN分类算法

package knn; import java.util.Collections; import java.util.HashMap; import java.util.Iterator; import java.util.List; import java.util.Map; import java.util.Set; public class KNN { //训练集 private List<KNNData> KNNDS = null; public KNN(List<KNNData> KNNDS) { this.setKNNDS(KNNDS); } //欧式距离 private static double disCal(KNNData i, KNNData td) { return Math.sqrt((i.c1 - td.c1)*(i.c1 - td.c1)+(i.c2 - td.c2)*(i.c2 - td.c2)); } private static String getMaxValueKey(int k, List<KNNData> ts){ //只保留前k个元素 while(ts.size() != k) { ts.remove(k); } String sKey; //保存key以及出现次数 HashMap<String,Integer> keySet = new HashMap<String,Integer>(); keySet.put(ts.get(0).type,1); for (int x = 1; x < ts.size(); x++) { sKey = ts.get(x).type; if (keySet.containsKey(sKey)) { keySet.put(sKey, keySet.get(sKey)+1); } else { keySet.put(sKey, 1); } } Set<Map.Entry<String,Integer>> set = keySet.entrySet(); Iterator<Map.Entry<String,Integer>> iter = set.iterator(); int mValue = 0; String mType = ""; while (iter.hasNext()){ Map.Entry<String,Integer> map = iter.next(); if (mValue < map.getValue()) { mType = map.getKey(); mValue = map.getValue(); } } return mType; } public static String knnCal(int k, KNNData i, List<KNNData> ts) { //保存距离 for (KNNData td : ts) { td.distance = disCal(i, td); } Collections.sort(ts); return getMaxValueKey(k, ts); } public List<KNNData> getKNNDS() { return KNNDS; } public void setKNNDS(List<KNNData> kNNDS) { KNNDS = kNNDS; } }