K-मीन्स क्लस्टरिंग

इनपुट:
std::vector<std::vector<double>> points = {
    {1.0, 1.0},
    {1.5, 2.0},
    {8.0, 8.0},
    {9.0, 8.5}
};
std::vector<std::vector<double>> centroids = {
    {0.0, 0.0},
    {10.0, 10.0}
};
long long iterations = 1;

अपेक्षित आउटपुट:
std::vector<std::vector<double>> expected = {
    {1.25, 1.5},
    {8.5, 8.25}
};

इनपुट:
double[][] points = new double[][] {
    new double[] {1.0, 1.0},
    new double[] {1.5, 2.0},
    new double[] {8.0, 8.0},
    new double[] {9.0, 8.5}
};
double[][] centroids = new double[][] {
    new double[] {0.0, 0.0},
    new double[] {10.0, 10.0}
};
long iterations = 1;

अपेक्षित आउटपुट:
double[][] expected = new double[][] {
    new double[] {1.25, 1.5},
    new double[] {8.5, 8.25}
};

इनपुट:
std::vector<std::vector<double>> points = {
    {0.0},
    {1.0},
    {10.0}
};
std::vector<std::vector<double>> centroids = {
    {0.0},
    {100.0}
};
long long iterations = 2;

अपेक्षित आउटपुट:
std::vector<std::vector<double>> expected = {
    {3.666667},
    {100.0}
};

इनपुट:
double[][] points = new double[][] {
    new double[] {0.0},
    new double[] {1.0},
    new double[] {10.0}
};
double[][] centroids = new double[][] {
    new double[] {0.0},
    new double[] {100.0}
};
long iterations = 2;

अपेक्षित आउटपुट:
double[][] expected = new double[][] {
    new double[] {3.666667},
    new double[] {100.0}
};