Answer:
Only the last number of each IP address will be unique(Correct)
Explanation:
Answer:
B. R is NP Hard
Explanation:
Given:
S is an NP complete problem
Q is not known to be in NP
R is not known to be in NP
Q is polynomial times reducible to S
S is polynomial times reducible to R
Solution:
NP complete problem has to be in both NP and NP-hard. A problem is NP hard if all problems in NP are polynomial time reducible to it.
Option B is correct because as given in the question S is an NP complete problem and S is polynomial times reducible to R.
Option A is not correct because R is not known to be in NP
Option C is not correct because Q is also not known to be in NP
Option D is not correct because Q because no NP-complete problem is polynomial time reducible to Q.
K-means can be used for hierarchical clustering by creating a hierarchical tree structure. This is done by setting the number of clusters to be created, and then running the k-means clustering algorithm for each level of the tree. For each level, the clusters created are then combined to form the next level of the tree. This process is repeated until the desired number of clusters has been created.
<h3>The Use of K-Means Clustering for Hierarchical Clustering</h3>
K-means clustering is a popular technique used in machine learning and data mining for partitioning data into clusters. It is a flat clustering algorithm, in which data points are grouped according to their similarity. While k-means clustering is suitable for partitioning data into a fixed number of clusters, it can also be used for hierarchical clustering. Hierarchical clustering is a clustering technique that creates a hierarchical tree structure, where each level of the tree is made up of clusters created by the k-means clustering algorithm.
The process of creating a hierarchical tree structure using k-means clustering is fairly straightforward. First, the number of clusters to be created is set, and then the k-means clustering algorithm is run for each level of the tree. For each level, the clusters created are then combined to form the next level of the tree until the desired number of clusters has been created. This process ensures that the clusters created are meaningful and have similar characteristics.
Learn more about k-means :
brainly.com/question/17241662
#SPJ4
Answer: Density is the mass of an object divided by its volume. Density often has units of grams per cubic centimeter (g/cm3). Remember, grams is a mass and cubic centimeters is a volume (the same volume as 1 milliliter).
Explanation:
#include <iostream>
#include <string>
int main(){
int number = 1;
while(number >= 1){
std::cin >> number;
if((number % 2) == 0){
std::cout << number << " ";
}
}
return 0;
}
