int main()
{
init_shogun_with_defaults();
// Create a StreamingAsciiFile from the training data
const char* train_file_name = "../data/train_densereal.light";
CStreamingAsciiFile* train_file = new CStreamingAsciiFile(train_file_name);
SG_REF(train_file);
// The bool value is true if examples are labelled.
// 1024 is a good standard value for the number of examples for the parser to hold at a time.
CStreamingDenseFeatures<float32_t>* train_features = new CStreamingDenseFeatures<float32_t>(train_file, true, 1024);
SG_REF(train_features);
// Create an OnlineLiblinear object from the features. The first parameter is 'C'.
COnlineLibLinear* svm = new COnlineLibLinear(1, train_features);
svm->set_bias_enabled(false); // Enable/disable bias
svm->train(); // Train
train_file->close();
// Now we want to test on other data
const char* test_file_name = "../data/fm_test_densereal.dat";
CStreamingAsciiFile* test_file = new CStreamingAsciiFile(test_file_name);
SG_REF(test_file);
// Similar, but 'false' since the file contains unlabelled examples
CStreamingDenseFeatures<float64_t>* test_features = new CStreamingDenseFeatures<float64_t>(test_file, false, 1024);
SG_REF(test_features);
// Apply on all examples and return a CLabels*
CRegressionLabels* test_labels = svm->apply_regression(test_features);
for (int32_t i=0; i<test_labels->get_num_labels(); i++)
SG_SPRINT("For example %d, predicted label is %f.\n", i, test_labels->get_label(i));
SG_UNREF(test_features);
SG_UNREF(test_labels);
SG_UNREF(test_file);
SG_UNREF(train_features);
SG_UNREF(train_file);
SG_UNREF(svm);
exit_shogun();
return 0;
}
int main(int argc, char* argv[])
{
init_shogun_with_defaults();
float64_t C = 1.0;
char *train_file_name = (char*)"../data/train_sparsereal.light";
char *test_file_name = (char*)"../data/test_sparsereal.light";
char filename_tmp[] = "test_labels.XXXXXX";
#ifdef _WIN32
int err = _mktemp_s(filename_tmp, strlen(filename_tmp)+1);
ASSERT(err == 0);
#else
int fd = mkstemp(filename_tmp);
ASSERT(fd != -1);
int retval = close(fd);
ASSERT(retval != -1);
#endif
char *test_labels_file_name = filename_tmp;
if (argc > 4) {
int32_t idx = 1;
C = atof(argv[idx++]);
train_file_name = argv[idx++];
test_file_name = argv[idx++];
test_labels_file_name = argv[idx++];
ASSERT(idx <= argc);
}
fprintf(stderr, "*** training file %s with C %g\n", train_file_name, C);
// Create an OnlineLiblinear object from the features. The first parameter is 'C'.
COnlineLibLinear *svm = new COnlineLibLinear(C);
svm->set_bias_enabled(true);
{
CTime train_time;
train_time.start();
// Create a StreamingAsciiFile from the training data
CStreamingAsciiFile *train_file = new CStreamingAsciiFile(train_file_name);
SG_REF(train_file);
// The bool value is true if examples are labelled.
// 1024 is a good standard value for the number of examples for the parser to hold at a time.
CStreamingSparseFeatures < float32_t > *train_features =
new CStreamingSparseFeatures < float32_t > (train_file, true, 1024);
SG_REF(train_features);
svm->set_features(train_features);
svm->train();
train_file->close();
SG_UNREF(train_file);
SG_UNREF(train_features);
train_time.stop();
SGVector<float32_t> w_now = svm->get_w().clone();
float32_t w_now_norm = SGVector<float32_t>::twonorm(w_now.vector, w_now.vlen);
uint64_t train_time_int = train_time.cur_time_diff();
fprintf(stderr,
"*** total training time: %llum%llus (or %.1f sec), #dim = %d, ||w|| = %f\n",
train_time_int / 60, train_time_int % 60, train_time.cur_time_diff(),
w_now.vlen, w_now_norm
);
}
{
CTime test_time;
test_time.start();
// Now we want to test on holdout data
CStreamingAsciiFile *test_file = new CStreamingAsciiFile(test_file_name);
SG_REF(test_file);
// Set second parameter to 'false' if the file contains unlabelled examples
CStreamingSparseFeatures < float32_t > *test_features =
new CStreamingSparseFeatures < float32_t > (test_file, true, 1024);
SG_REF(test_features);
// Apply on all examples and return a CBinaryLabels*
CBinaryLabels *test_binary_labels = svm->apply_binary(test_features);
SG_REF(test_binary_labels);
test_time.stop();
uint64_t test_time_int = test_time.cur_time_diff();
fprintf(stderr, "*** testing took %llum%llus (or %.1f sec)\n",
test_time_int / 60, test_time_int % 60, test_time.cur_time_diff());
SG_UNREF(test_features);
SG_UNREF(test_file);
// Writing labels for evaluation
fprintf(stderr, "*** writing labels to file %s\n", test_labels_file_name);
FILE* fh = fopen(test_labels_file_name, "wb");
ASSERT(fh);
for (int32_t j = 0; j < test_binary_labels->get_num_labels(); j++)
fprintf(fh, "%d\n", test_binary_labels->get_int_label(j));
fclose(fh);
SG_UNREF(test_binary_labels);
unlink(test_labels_file_name);
}
SG_UNREF(svm);
exit_shogun();
return 0;
}
