Answer:
#include <iostream>
using namespace std;
void MinMax(int x,int y,int z,int *max,int *min)
{
int big,small;
if((x>y)&&(x>z)) //to check for maximum value
big=x;
else if((y>x)&&(y>z))
big=y;
else
big=z;
if((x<y)&&(x<z)) //to check for minimum value
small=x;
else if((y<x)&&(y<z))
small=y;
else
small=z;
*max=big; //pointer pointing to maximum value
*min=small; //pointer pointing to minimum value
}
int main()
{
int big,small;
MinMax(43,29,100,&big,&small);
cout<<"Max is "<<big<<"\nMin is "<<small; //big and small variables will get value from method called
return 0;
}
OUTPUT :
Max is 100
Min is 29
Explanation:
When the method is called from first three integers maximum will be found using the conditions imposed and maximum value will be found and similarly will happen with the minimum value.
Answer:
getline(cin, address);
Explanation:
Given
String object: address
Required
Statement that reads the entire line
The list of given options shows that the programming language is c++.
Analysing each option (a) to (e):
a. cin<<address;
The above instruction will read the string object until the first blank space.
Take for instance:
The user supplied "Lagos state" as input, only "Lagos" will be saved in address using this option.
b. cin address:
This is an incorrect syntax
c. getline(cin,address);
Using the same instance as (a) above, this reads the complete line and "Lagos state" will be saved in variable address
d. cin.get(address);
address is created as a string object and the above instruction will only work for character pointers (i.e. char*)
<em>From the above analysis, option (c) is correct.</em>
Answer:
The third point i.e " Use an alternating least squares (ALS) algorithm to create a collaborative filtering solution" is the correct answer .
Explanation:
The Alternating Less Squares is the different approach that main objective to enhancing the loss function.The Alternating Less Squares process divided the matrix into the two factors for optimizing the loss .The divided of two factor matrix is known as item matrix or the user matrix.
- As we have to build the machine learning model which proposes restaurants to restaurants that are based on the customer information and the prior restaurant reviews the alternating least squares is the best model to implement this .
- All the other options are not the correct model also they are not related to given scenario that's why they are incorrect options.
True
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