Answer and Explanation:
Some of the advantages of using the F measure (weighted harmonic mean) over using the Precision & Recall when evaluating an IR system performance are as follows-
- Precision quantifies the number of positive class predictions that actually belong to the positive class.
- Recall quantifies the number of positive class predictions made out of all positive examples in the dataset.
- F-Measure provides a single score that balances both the concerns of precision and recall in one number.
- A measure that combines precision and recall is the harmonic mean of precision and recall, the traditional F-measure or balanced F-score:
F=2((precision.recall)/(precision+recall))
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Answer:
// This program is written in C++
// Comments are used for explanatory purpose
// Program starts here
#include<iostream.h>
#include<stdlib.h>
int main()
{
// Declare variables
int num, selectno;
string status;
randomize();
//Generate random number;
num=rand()%10000;
// Prompt to guess a number
cout<<"You have only 10 tries\nTake a guess: ";
int tries = 0;
while (tries != 10)
{
cin>>selectno;
if(selectno == num){
cout<<"You passed at the "<<count+1<<" attempt";
tries = 10;
}
else
{
cout<<"You failed. Take another guess\n You have "<<10 - count + 1 <<" attempts";
}
tries++;
if(tries >= 10)
{
break;
}
}
return 0;
}
The correct answer is known as a "query".
When you ask a lot of complex questions , which uses comparison operators, that is called a query. A query refers to the <span>exact request for </span>data retrieval<span> with the use of database and information systems. </span>
Answer:
A. C to clear any previous calculations.
hope it helps...
