Reputation: 107
I'm currently coding the cost function of logistic regression using JAMA lib. but it's not working. and I don't know why. it supposed to return a value: 0.6743
public matrix cost () {
double[][] sigmoid = sigmoidFunction().getArray();
double[][] sigmoid2 = sigmoidFunction().getArray();
int m = sigmoidFunction().getRowdimension();
int n = sigmoidFunction().getColdimension();
for (int i = 0; i<m; i++) {
for (int j =0; j< n; j++) {
sigmoid[i][j] = Math.log(sigmoid[i][j]);
}
}
for (int i = 0; i<m; i++) {
for (int j =0; j< n; j++) {
sigmoid2[i][j] = Math.log(1-sigmoid2[i][j]);
}
}
matrix regularized = theta.transpose().times(theta);
double[][] reg = regularized.getArray();
for(int i = 0; i< regularized.getRowdimension(); i++ ) {
for (int j = 0; j< regularized.getColdimension(); j++) {
reg[i][j] = lambda/(2*m) * (reg[i][j]);
}
}
regularized = new matrix(reg);
matrix log_hx = new matrix(sigmoid);
matrix log1_hx = new matrix(sigmoid2);
matrix y_1 = Y;
y_1 = y_1.transpose().subtract(1);
Y = Y.uminus();
Y= Y.transpose();
//J = 1/m * (-y' * log(hx) - (1-y)' * log(1-hx))
matrix J = Y.times(log_hx).subtract(y_1.times(log1_hx));
double [][] cost = J.getArray();
for(int i = 0; i< J.getRowdimension(); i++ ) {
for (int j =0; j< J.getColdimension(); j++) {
cost[i][j]= 1/m * cost[i][j];
}
}
//J = new matrix(cost);
//J.addEquals(regularized);
return J;
}
}
when I return the matrix J as seen above, it returns 0.0 . but when I directly return Y.times(log_hx).subtract(y_1.times(log1_hx)), it magically returns a value of 3.3715. which is correct when it is not multiplied by 1/m and added by regularization
Upvotes: 1
Views: 606
Reputation: 107
double [][] cost = J.getArray();
for(int i = 0; i< J.getRowdimension(); i++ ) {
for (int j =0; j< J.getColdimension(); j++) {
cost[i][j]= 1/m * cost[i][j];
}
double[][] cost = J.getArray();
double cost_temp = cost[0][0]*1/m;
J.set_element(0,0,cost_temp);
J.addEquals(regularized);
return J;
Upvotes: 1