Answer:
Compare the predictions in terms of the predictors that were used, the magnitude of the difference between the two predictions, and the advantages and disadvantages of the two methods.
Our predictions for the two models were very simmilar. A difference of $32.78 (less than 1% of the total price of the car) is statistically insignificant in this case. Our binned model returned a whole number while the full model returned a more “accurate” price, but ultimately it is a wash. Both models had comparable accuracy, but the full regression seemed to be better trained. If we wanted to use the binned model I would suggest creating smaller bin ranges to prevent underfitting the model. However, when considering the the overall accuracy range and the car sale market both models would be
Explanation:
Answer:
antivirus.......hope this answers your question
Zeros and ones
Hope the helps
Godspeed
True, sites such as kickstarter and just giving are fantastic examples of such.
Answer:
#include <iostream>
#include <cstdlib>
using namespace std;
int m, n;
void transpose(int matrix[]){
int transp[m][n];
for (int i = 0; i < n; i++){
for (int j = 0; j < m; j++){
transp[j][i] = matrix[i][j];
cout<< transp[j][i]<< " ";
}
cout<< "\n";
}
}
int main(){
cout<< "Enter the value for n: ";
cin>> n;
cout>> "Enter the value for m: ";
cin>> m;
int mymatrix[n][m];
for (int i = 0; i < n; i++){
for (int j = 0; j < m; j++){
mymatrix[i][j] = (rand() % 50);
}
}
transpose(mymatrix);
}
Explanation:
The C source code defined a void transpose function that accepts a matrix or a two-dimensional array and prints the transpose on the screen. The program gets user input for the row (n) and column (m) length of the arrays. The C standard library function rand() is used to assign random numbers to the array items.
