\log \left(1 + e^{x}\right) - x \cdot y\left(e^{\log \left(\log \left(\sqrt{1 + e^{x}}\right)\right)} + \log \left(\sqrt{1 + e^{x}}\right)\right) - x \cdot ydouble f(double x, double y) {
double r149168 = 1.0;
double r149169 = x;
double r149170 = exp(r149169);
double r149171 = r149168 + r149170;
double r149172 = log(r149171);
double r149173 = y;
double r149174 = r149169 * r149173;
double r149175 = r149172 - r149174;
return r149175;
}
double f(double x, double y) {
double r149176 = 1.0;
double r149177 = x;
double r149178 = exp(r149177);
double r149179 = r149176 + r149178;
double r149180 = sqrt(r149179);
double r149181 = log(r149180);
double r149182 = log(r149181);
double r149183 = exp(r149182);
double r149184 = r149183 + r149181;
double r149185 = y;
double r149186 = r149177 * r149185;
double r149187 = r149184 - r149186;
return r149187;
}




Bits error versus x




Bits error versus y
Results
| Original | 0.5 |
|---|---|
| Target | 0.1 |
| Herbie | 1.0 |
Initial program 0.5
rmApplied add-sqr-sqrt1.4
Applied log-prod1.0
rmApplied add-exp-log1.0
Final simplification1.0
herbie shell --seed 2019195 +o rules:numerics
(FPCore (x y)
:name "Logistic regression 2"
:herbie-target
(if (<= x 0.0) (- (log (+ 1.0 (exp x))) (* x y)) (- (log (+ 1.0 (exp (- x)))) (* (- x) (- 1.0 y))))
(- (log (+ 1.0 (exp x))) (* x y)))