在kNN算法中改變k的值 - Java

Question

我已經應用KNN算法對手寫數字進行分類。這些數字最初是8 * 8的矢量格式，並且被拉伸以形成矢量1 * 64 ..

因爲它代表我應用kNN算法，但只使用k = 1。我不完全知道如何在嘗試了幾個我不斷拋出錯誤的東西后，改變k值。如果任何人都可以幫助我朝着正確的方向前進，那麼我將非常感激。訓練數據集可以找到here和驗證集合here。

ImageMatrix.java

import java.util.*; 

public class ImageMatrix { 
    private int[] data; 
    private int classCode; 
    private int curData; 
public ImageMatrix(int[] data, int classCode) { 
    assert data.length == 64; //maximum array length of 64 
    this.data = data; 
    this.classCode = classCode; 
} 

    public String toString() { 
     return "Class Code: " + classCode + " Data :" + Arrays.toString(data) + "\n"; //outputs readable 
    } 

    public int[] getData() { 
     return data; 
    } 

    public int getClassCode() { 
     return classCode; 
    } 
    public int getCurData() { 
     return curData; 
    } 



} 

ImageMatrixDB.java

import java.util.*; 
import java.io.*; 
import java.util.ArrayList; 
public class ImageMatrixDB implements Iterable<ImageMatrix> { 
    private List<ImageMatrix> list = new ArrayList<ImageMatrix>(); 

    public ImageMatrixDB load(String f) throws IOException { 
     try (
      FileReader fr = new FileReader(f); 
      BufferedReader br = new BufferedReader(fr)) { 
      String line = null; 

      while((line = br.readLine()) != null) { 
       int lastComma = line.lastIndexOf(','); 
       int classCode = Integer.parseInt(line.substring(1 + lastComma)); 
       int[] data = Arrays.stream(line.substring(0, lastComma).split(",")) 
            .mapToInt(Integer::parseInt) 
            .toArray(); 
       ImageMatrix matrix = new ImageMatrix(data, classCode); // Classcode->100% when 0 -> 0% when 1 - 9.. 
       list.add(matrix); 
      } 
     } 
     return this; 
    } 

    public void printResults(){ //output results 
     for(ImageMatrix matrix: list){ 
      System.out.println(matrix); 
     } 
    } 


    public Iterator<ImageMatrix> iterator() { 
     return this.list.iterator(); 
    } 

    /// kNN implementation /// 
    public static int distance(int[] a, int[] b) { 
     int sum = 0; 
     for(int i = 0; i < a.length; i++) { 
      sum += (a[i] - b[i]) * (a[i] - b[i]); 
     } 
     return (int)Math.sqrt(sum); 
    } 


    public static int classify(ImageMatrixDB trainingSet, int[] curData) { 
     int label = 0, bestDistance = Integer.MAX_VALUE; 
     for(ImageMatrix matrix: trainingSet) { 
      int dist = distance(matrix.getData(), curData); 
      if(dist < bestDistance) { 
       bestDistance = dist; 
       label = matrix.getClassCode(); 
      } 
     } 
     return label; 
    } 


    public int size() { 

     return list.size(); //returns size of the list 

     } 


    public static void main(String[] argv) throws IOException { 
     ImageMatrixDB trainingSet = new ImageMatrixDB(); 
     ImageMatrixDB validationSet = new ImageMatrixDB(); 
     trainingSet.load("cw2DataSet1.csv"); 
     validationSet.load("cw2DataSet2.csv"); 
     int numCorrect = 0; 
     for(ImageMatrix matrix:validationSet) { 
      if(classify(trainingSet, matrix.getData()) == matrix.getClassCode()) numCorrect++; 
     } //285 correct 
     System.out.println("Accuracy: " + (double)numCorrect/validationSet.size() * 100 + "%"); 
     System.out.println(); 
    } 

Answer 1

在爲環分類你正在努力尋找訓練的例子，是最接近測試點。您需要將代碼切換爲最接近測試數據的訓練點的K。然後你應該爲這些K點中的每一個調用getClassCode，並找出其中多數類（即最常見的）類代碼。 classify將返回您找到的主要類代碼。

您可以以任何適合您需要的方式打破關係（即擁有分配給相同數量訓練數據的2+最頻繁分類代碼）。

我真的沒有經驗的Java，但只是通過環顧語言參考，我想出了下面的實現。

public static int classify(ImageMatrixDB trainingSet, int[] curData, int k) { 
    int label = 0, bestDistance = Integer.MAX_VALUE; 
    int[][] distances = new int[trainingSet.size()][2]; 
    int i=0; 

    // Place distances in an array to be sorted 
    for(ImageMatrix matrix: trainingSet) { 
     distances[i][0] = distance(matrix.getData(), curData); 
     distances[i][1] = matrix.getClassCode(); 
     i++; 
    } 

    Arrays.sort(distances, (int[] lhs, int[] rhs) -> lhs[0]-rhs[0]); 

    // Find frequencies of each class code 
    i = 0; 
    Map<Integer,Integer> majorityMap; 
    majorityMap = new HashMap<Integer,Integer>(); 
    while(i < k) { 
     if(majorityMap.containsKey(distances[i][1])) { 
      int currentValue = majorityMap.get(distances[i][1]); 
      majorityMap.put(distances[i][1], currentValue + 1); 
     } 
     else { 
      majorityMap.put(distances[i][1], 1); 
     } 
     ++i; 
    } 

    // Find the class code with the highest frequency 
    int maxVal = -1; 
    for (Entry<Integer, Integer> entry: majorityMap.entrySet()) { 
     int entryVal = entry.getValue(); 
     if(entryVal > maxVal) { 
      maxVal = entryVal; 
      label = entry.getKey(); 
     } 
    } 

    return label; 
} 

所有你需要做的是將ķ作爲參數。但請記住，上面的代碼不能以特定的方式處理關係。