The program is an illustration of string manipulations
<h3>What are string manipulations?</h3>
String manipulations include calculating the lengths of strings and also performing several operations on the string
<h3>The actual program</h3>
The complete program in C++ is as follows:
#include <iostream>
using namespace std;
int main(){
string passwordStr;
cin>>passwordStr;
if(passwordStr.length() <= 7){
cout<<"Valid";
}
else{
cout<<"Invalid";
}
return 0;
}
Read more string manipulation at:
brainly.com/question/14284563
Loop takes only positive numbers and terminates once it encounters a negative numbers.
Answer and Explanation:
Using javascript:
Var positiveInt= window.prompt("insert positive integer");
While(positiveInt>=0){
Alert("a positive integer");
Var positiveInt= window.prompt("insert positive integer");
}
Or we use the do...while loop
Var positiveInt= window.prompt("insert positive integer");
do{
Var positiveInt= window.prompt("insert positive integer");
}
While (positiveInt>=0);
The above program in javascript checks to see if the input number is negative or positive using the while loop condition and keeps executing with each input until it gets a negative input
Answer:
D) Identifying Subgroups
Explanation:
In data Analytics, a third variable also known as a confounding variable, is a variable that "sits in-between", it has influence on both the independent variable and dependent variable. If this "third variable" is not properly handled, the result of the anlysis will yeild incorrect values. identifying subgroups in a dataset is important for undertanding it
Answer:
Collaborative filtering
Explanation:
This is one out of five on the Recommender system apart from most popular items, Association and Market Basket based Analysis, Content-based analysis, self and hybrid analysis where we use both content-based and collaborative based approach together. And the Recommender system is a very important topic in Data science. For this question, remember that Collaborative filtering focuses on user and various other user's choices which are mathematically alike to concerned users, and which we find with the study of a large data set. Thus, we can predict from our above study that what are going to be likes of concerned users, and at the item level, whether that item will be liked by the concerned user or not. And this is prediction, and we use this approach in Machine learning these days. For this question, and as mentioned in question the requirements, answer is Collaborative filtering.
Answer:
The answer is "Option D".
Explanation:
OLAP reports stands for Online Analytical Processing reports, These reports provide a platform that behind many application use in Business Intelligence. and other options are incorrect that can be described as follows:
- In option A, It is used to store the data into the OLAP report, that's why it is not correct.
- In option B, It is software that is used for analytics data, that's why it is not correct.
- In option C, It is used for finding index values in the 2D array that's why it is not correct.
