Changeset 1865

Timestamp:

Mar 16, 2009, 12:36:36 PM (15 years ago)

Author:

Peter

Message:

adding another test and fixing prediction when having empty training classes. closes #269

Location:

trunk

Files:

• test/svm_multi_class_test.cc (modified) (3 diffs)
• yat/classifier/SvmMultiClass.cc (modified) (1 diff)

trunk/test/svm_multi_class_test.cc

@@ -35 +35 @@
 void test_construction(test::Suite&);
 void test_predict(test::Suite&);
+void test_predict2(test::Suite&);
 
 int main( int argc, char* argv[])
@@ -42 +43 @@
   test_construction(suite);
   test_predict(suite);
+  test_predict2(suite);
 
   return suite.return_value();
@@ -111 +113 @@
   }
 }
+
+void test_predict2(test::Suite& suite)
+{
+  using namespace classifier;
+  std::string file = test::filename("data/sorlie_centroid_data.txt");
+  std::ifstream is(file.c_str());
+  suite.err() << "load data `" << file << "'" << std::endl;
+  MatrixLookupWeighted data(is, '\t');
+  is.close();
+  PolynomialKernelFunction linear;
+  suite.err() << "calculating kernel" << std::endl;
+  Kernel_SEV kernel_raw(data, linear);
+  file = test::filename("data/sorlie_centroid_classes.txt");
+  suite.err() << "load classes `" << file << "'" << std::endl;
+  is.open(file.c_str());
+  Target target(is);
+  is.close();
+
+  std::vector<size_t> index;
+  for (size_t i=0; i<50; ++i)
+    index.push_back(i);
+  for (size_t i=70; i<79; ++i)
+    index.push_back(i);
+  utility::Index train_index(index);
+  
+  Target target_train(target, train_index);
+  KernelLookup kernel_train(kernel_raw, train_index, train_index);
+  SvmMultiClass svm;
+  suite.err() << "training svm" << std::endl;
+  svm.train(kernel_train, target_train);
+
+  index.clear();
+  for (size_t i=50; i<70; ++i)
+    index.push_back(i);
+  utility::Index test_index(index);
+
+  KernelLookup kernel_test(kernel_raw, train_index, test_index);
+  utility::Matrix result;
+  suite.err() << "Predicting on test data" << std::endl;
+  svm.predict(kernel_test, result);
+
+  if (!suite.add(result.rows()==5 && result.columns()==20)) {
+    suite.err() << "ERROR: incorrect dimension in result Matrix\n"
+                << "found " << result.rows() << "x" << result.columns() << "\n"
+                << "expected 5x79\n";
+  }
+  if (!suite.add(std::isnan(result(3, 0))) ) {
+    suite.err() << "ERROR: expected result(4,0) to be nan\n"
+                << "  found " << result(4,0) << std::endl;
+  }
+
+}
+

trunk/yat/classifier/SvmMultiClass.cc

@@ -69 +69 @@
                       std::numeric_limits<double>::quiet_NaN());
     for (size_t i=0; i<svm_.size(); ++i) {
-      yat::utility::Matrix tmp;
-      svm_[i].predict(input, tmp);
-      prediction.row_view(i) = tmp.row_const_view(0);
+      if (svm_[i].trained()) {
+        yat::utility::Matrix tmp;
+        svm_[i].predict(input, tmp);
+        prediction.row_view(i) = tmp.row_const_view(0);
+      }
     }