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authorPatrick Simianer <p@simianer.de>2011-09-24 23:46:49 +0200
committerPatrick Simianer <p@simianer.de>2011-09-24 23:46:49 +0200
commit5e1ab3481551607f1c2a10027049044cd41f78ab (patch)
treeb89cc3587f2e5d34f14f4b977f8a0909f62fe8e1 /dtrain/test/logreg/log_reg.cc
parent5584f300821e20369c25343222cd0e8faa393523 (diff)
cleaning up
Diffstat (limited to 'dtrain/test/logreg/log_reg.cc')
-rw-r--r--dtrain/test/logreg/log_reg.cc39
1 files changed, 39 insertions, 0 deletions
diff --git a/dtrain/test/logreg/log_reg.cc b/dtrain/test/logreg/log_reg.cc
new file mode 100644
index 00000000..ec2331fe
--- /dev/null
+++ b/dtrain/test/logreg/log_reg.cc
@@ -0,0 +1,39 @@
+#include "log_reg.h"
+
+#include <vector>
+#include <cmath>
+
+#include "sparse_vector.h"
+
+using namespace std;
+
+double LogisticRegression::ObjectiveAndGradient(const SparseVector<double>& x,
+ const vector<TrainingInstance>& training_instances,
+ SparseVector<double>* g) const {
+ double cll = 0;
+ for (int i = 0; i < training_instances.size(); ++i) {
+ const double dotprod = training_instances[i].x_feature_map.dot(x); // TODO no bias, if bias, add x[0]
+ double lp_false = dotprod;
+ double lp_true = -dotprod;
+ if (0 < lp_true) {
+ lp_true += log1p(exp(-lp_true));
+ lp_false = log1p(exp(lp_false));
+ } else {
+ lp_true = log1p(exp(lp_true));
+ lp_false += log1p(exp(-lp_false));
+ }
+ lp_true *= -1;
+ lp_false *= -1;
+ if (training_instances[i].y) { // true label
+ cll -= lp_true;
+ (*g) -= training_instances[i].x_feature_map * exp(lp_false);
+ // (*g)[0] -= exp(lp_false); // bias
+ } else { // false label
+ cll -= lp_false;
+ (*g) += training_instances[i].x_feature_map * exp(lp_true);
+ // g += corpus[i].second * exp(lp_true);
+ }
+ }
+ return cll;
+}
+