removed some quirks, less boost, prettier code, score_t

4 files changed, 0 insertions, 79 deletions

diff --git a/dtrain/test/logreg/bin_class.cc b/dtrain/test/logreg/bin_class.cc
deleted file mode 100644
index 19bcde25..00000000
--- a/dtrain/test/logreg/bin_class.cc
+++ /dev/null
@@ -1,4 +0,0 @@
-#include "bin_class.h"
-
-Objective::~Objective() {}
-
diff --git a/dtrain/test/logreg/bin_class.h b/dtrain/test/logreg/bin_class.h
deleted file mode 100644
index 3466109a..00000000
--- a/dtrain/test/logreg/bin_class.h
+++ /dev/null
@@ -1,22 +0,0 @@
-#ifndef _BIN_CLASS_H_
-#define _BIN_CLASS_H_
-
-#include <vector>
-#include "sparse_vector.h"
-
-struct TrainingInstance {
-  // TODO add other info? loss for MIRA-type updates?
-  SparseVector<double> x_feature_map;
-  bool y;
-};
-
-struct Objective {
-  virtual ~Objective();
-
-  // returns f(x) and f'(x)
-  virtual double ObjectiveAndGradient(const SparseVector<double>& x,
-                  const std::vector<TrainingInstance>& training_instances,
-                  SparseVector<double>* g) const = 0;
-};
-
-#endif
diff --git a/dtrain/test/logreg/log_reg.cc b/dtrain/test/logreg/log_reg.cc
deleted file mode 100644
index ec2331fe..00000000
--- a/dtrain/test/logreg/log_reg.cc
+++ /dev/null
@@ -1,39 +0,0 @@
-#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;
-}
-
diff --git a/dtrain/test/logreg/log_reg.h b/dtrain/test/logreg/log_reg.h
deleted file mode 100644
index ecc560b8..00000000
--- a/dtrain/test/logreg/log_reg.h
+++ /dev/null
@@ -1,14 +0,0 @@
-#ifndef _LOG_REG_H_
-#define _LOG_REG_H_
-
-#include <vector>
-#include "sparse_vector.h"
-#include "bin_class.h"
-
-struct LogisticRegression : public Objective {
-  double ObjectiveAndGradient(const SparseVector<double>& x,
-                              const std::vector<TrainingInstance>& training_instances,
-                              SparseVector<double>* g) const;
-};
-
-#endif