Converged centroids now accessible in api

Cluster.cpp

@@ -167,6 +167,20 @@ bool Cluster::step() {
   return true; // return true if no change
 }
 
+float** Cluster::centroids() {
+  assert(*_centroids);
+  int numParams = (*_centroids)->size();
+  float** c = new float*[_k];
+  for (int i = 0; i < _k; i++) {
+    c[i] = new float[numParams];
+    float* features = _centroids[i]->features();
+    for (int j = 0; j < numParams; j++) {
+      c[i][j] = features[j];
+    }
+  }
+  return c;
+}
+
 void Cluster::updateCentroids() {
   // Examine first training example to get feature count, etc 
   if (!_data.size())
@@ -211,3 +225,17 @@ void Cluster::updateUntilConvergence() {
   }
 }
 
+int Cluster::classify(Data *data) {
+  float minDist = FLT_MAX;
+  int classification = -1;
+  for (int i = 0; i < _k; i++) {
+    float dist = distance(data, _centroids[i]);
+    if (dist < minDist) {
+      minDist = dist;
+      classification = i;
+    }
+  }
+  cout << "Classification: " << classification << endl;
+  return classification;
+}
+

Cluster.h

@@ -8,6 +8,8 @@ class Cluster {
   Cluster(int k, vector<Data*> data);
   ~Cluster();
   void update();
+  int classify(Data *data);
+  float** centroids();
 
 private:
   vector<Data*> _data;              // Training set (unsupervised)

Data.h

@@ -6,7 +6,7 @@
 #include <vector>
 #include <cassert>
 
-#define PRINT_LOG
+//#define PRINT_LOG
 
 #ifdef PRINT_LOG
 #define LOG(string, ...) printf(string, __VA_ARGS__)

Makefile

@@ -3,7 +3,7 @@ CC = g++
 SRC = main.cpp 
 OBJ = Data.o SupervisedData.o BatchDescentLearner.o StochasticLearner.o Learner.o Cluster.o
 CFLAGS = -Werror -g -ggdb
-LDFLAGS = 
+LDFLAGS = -lreadline
 
 all: vasco
 

main.cpp

@@ -44,35 +44,25 @@ int main() {
   if (!data.size())
     return 1;
 
-  Cluster learner(3, data);
-  learner.update();
+  // Repeatedly classify
 
-  bool quit = false;
-  while (!quit) {
-    char* line = (char*)malloc(sizeof(char)*100);
-    size_t nbytes = 99;
-    printf(">> ");
-    getline(&line, &nbytes, stdin);
-    for (int i = 0; i < strlen(line); i++)
-      if (line[i] == '\n')
-        line[i] = '\0';
-    if (!strcmp(line, "quit")) {
-      quit = true;
-    }
-    else {
-      float params[4] = {0};
-      stringstream ss(line);
-      for (int i = 0; i < 4; i++) {
-        ss >> params[i];
-      }
+  for (int p = 0; p < 10; p++) {
+    Cluster learner(3, data);
+    learner.update();
+    float** centroids = learner.centroids();
 
-      Data *newData = new Data(num_features);
-      newData->setFeatures(num_features, params);
-      learner.classify(newData);
-      free(newData);
+    for (int i = 0; i < 3; i++) {
+      cout << "Centroid " << i << endl;
+      for (int j = 0; j < 4; j++) {
+        cout << "\t" << centroids[i][j];
+      }
+      cout << endl;
     }
 
-    free(line);
+    for (int i = 0; i < 3; i++)
+      free(centroids[i]);
+    free(centroids);
+    cout << endl << endl;
   }
 
   for (int i = 0; i < set_size; i++) {