CODEWITHSUNDEEP
c++machine-learningclassificationknnkdtree
A-ar
A-ar

Reputation: 76

How to implement K-NN classification from a k-d tree?

I'm trying to write the code for K-NN classification using k-d tree without using any libraries. So far I have been able to write the code for k-d tree but I cant seem to understand how do I find the k nearest neighbors once the tree has been formed from a training set. k-d tree code:

#include<bits/stdc++.h> 
using namespace std; 

const int k = 2; // 2-dimensions 

struct Node 
{ 
    int point[k]; 
    Node *left, *right; 
}; 

struct Node* newNode(int arr[]) 
{ 
    struct Node* temp = new Node; 

    for (int i=0; i<k; i++) 
    temp->point[i] = arr[i]; 

    temp->left = temp->right = NULL; 
    return temp; 
} 
// Inserts a new node and returns root of modified tree
Node *insertRec(Node *root, int point[], unsigned depth) 
{ 
    if (root == NULL) 
    return newNode(point);  
    unsigned cd = depth % k; 
    if (point[cd] < (root->point[cd])) 
        root->left = insertRec(root->left, point, depth + 1); 
    else
        root->right = insertRec(root->right, point, depth + 1); 

    return root; 
} 
// Function to insert a new point with given point and return new root
Node* insert(Node *root, int point[]) 
{ 
    return insertRec(root, point, 0); 
} 

// driver 
int main() 
{ 
    struct Node *root = NULL; 
    int points[][k] = {{3, 6}, {17, 15}, {13, 15}, {6, 12}, 
                    {9, 1}, {2, 7}, {10, 19}}; 
    int n = sizeof(points)/sizeof(points[0]); 
    for (int i=0; i<n; i++) 
    root = insert(root, points[i]); 
    return 0; 
}

Upvotes: 0

Views: 99

Answers (1)

Matthieu Brucher
Matthieu Brucher

Reputation: 22023

First don't use <bits/stdc++.h>. That's wrong.

To find the k closest elements, you need to go through the tree in a way that will traverse the closest elements first. Then, if you don't have enough elements, go and traverse the ones that are further.

I won't write the code here, just pseudo code (because I already built one a long time ago):

list l; # list of the elements, sorted by distance
heap p; # heap of nodes to traverse, sorted by distance

p.push(root)
while (!p.empty())
{
    node = p.pop(); # Get a new node
    d = distance(point, node); # compute the closest distance from the point to the node
    if(l.empty() or distance(point, l.back()) > d)
    {
        add(node->left); # iteration on subnodes
        add(node->right);
        l.push(points); # Add points from the current node
    }
    l.pop_elements(k); # pop elements to keep only k
}

Upvotes: 1

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