This repository contains a simple C++ implementation of a KD (K-Dimensional) tree, a data structure used for efficient searching in multidimensional spaces. The code defines functions to create, insert, search, and delete points in the KD tree.

To use the KD tree, follow these steps:

1. Include the necessary header file:

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

2. Define the dimensionality of the points (in this case, k=2) and create a structure to represent a node in the KD tree.

3. Create a new KD tree node using the newNode function, passing the coordinates of the point.

4. Insert points into the KD tree using the insert function.

5. Search for points in the KD tree using the search function.

6. Delete points from the KD tree using the deleteNode function.

This function creates a new KD tree node with the given coordinates.

This function inserts a new point into the KD tree and returns the modified root of the tree.

This function searches for a point in the KD tree and returns true if the point is found, otherwise false.

This function deletes a given point from the KD tree and returns the modified root of the tree.

This function finds the minimum point along the d'th dimension in the KD tree.

This function finds the node with the minimum value along the d'th dimension among the three given nodes.

This utility function copies the coordinates of one point into another.

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

// ... (Rest of the code, as provided)

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]);

    // Inserting points into the KD tree
    for (int i=0; i<n; i++)
       root = insert(root, points[i]);

    // Searching for a point in the KD tree
    int searchPoint[k] = {6, 12};
    bool isFound = search(root, searchPoint);
    if (isFound)
        cout << "Point is present in the KD tree." << endl;
    else
        cout << "Point is not found in the KD tree." << endl;

    // Deleting a point from the KD tree
    int deletePoint[k] = {13, 15};
    root = deleteNode(root, deletePoint);

    return 0;
}

This is a simplified version of the KD tree implementation and may not be optimized for large datasets or real-world scenarios. Use it as a reference and consider further optimizations and error handling for your specific use case.