Answer:
See Explanation
Explanation:
Your program is correct and doesn't need an attachment.
However, there's a mismatch in placement of curly braces in your program
{
}
I've made corrections to that and I've added the corrected program as an attachment.
Aside that, there's no other thing to be corrected in your program.
Use another compiler to compile your program is you are not getting the required output.
Answer:
#include <iostream>
#include <cstdlib>
#include <ctime>
using namespace std;
int main(){
int n;
cout<< "Enter the row and column length: ";
cin>> n;
int array_one[n][n];
int array_transpose[n][n];
for (int i = 0; i < n; i++){
for (int j= 0; j < n; j++){
srand((unsigned) time(0));
array_one[i][j] = (rand() % 4000)
array_transpose[j][i] = array_one[i][j];
}
}
}
Explanation:
The C source code has three variables, 'array_one', array_transpose' (both of which are square 2-dimensional arrays), and 'n' which is the row and column length.
The program loops n time for each nth number of the n size to assign value to the two-dimensional array_one. the assign values to the array_transpose, reverse the 'i' and 'j' values to the two for statements for array_one to 'j' and 'i'.
Answer:
1. Export
2. Create PDF/XPS document
3. Standard
4. Click Publish
Explanation:
I got wrong on edg and found the correct answer
One of the most often used methods of linear dimension reduction is principal component analysis (PCA). It can be used both on its own and as a starting point for further dimension reduction techniques.
By projecting the data onto a set of orthogonal axes, the projection-based PCA approach changes the data. An unsupervised linear transformation method known as Principal Component Analysis (PCA) is frequently utilized in a variety of domains, most notably for feature extraction and dimensionality reduction. Data compression, made possible by dimensionality reduction, results in less storage space being used. It speeds up computation. It also aids in removing any extraneous features. Since PCA is a variance-maximizing activity, normalization is crucial. our original data is projected in a manner that maximizes variance.
Learn more about dimension here-
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In computer science, a list or sequence is an abstract data type that represents a countable number of ordered values, where the same value may occur more than once.
A graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from mathematics.
A table is a collection of related data held in a structured format within a database. It consists of columns and rows.
A chart, also called a graph, is a graphical representation of data, in which "the data is represented by symbols, such as bars in a bar chart, lines in a line chart, or slices in a pie chart.