本文整理汇总了C++中ME_Model::get_class_label方法的典型用法代码示例。如果您正苦于以下问题：C++ ME_Model::get_class_label方法的具体用法？C++ ME_Model::get_class_label怎么用？C++ ME_Model::get_class_label使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类ME_Model的用法示例。
在下文中一共展示了ME_Model::get_class_label方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: classify_samples
RcppExport SEXP classify_samples(int nrows, int ncols, vector<double> ia, vector<string> ja, vector<double> ra, string model_data) {
new_model();
model.load_from_string(model_data);
vector<string> results;
vector<string> probability_names;
NumericMatrix probability_matrix(nrows,model.num_classes());
for (int i=0; i < nrows; i++) { // for each document
//Rprintf("Document %d\n",i); // debug output
ME_Sample newSample; // create new sample for code
for (int j=ia[i]-1; j < ia[i+1]-1; j++) { // for each feature
newSample.add_feature(ja[j],ra[j]);
}
vector<double> prob = model.classify(newSample);
for (int k=0; k < model.num_classes(); k++) {
probability_matrix(i,k) = prob[k];
}
results.push_back(newSample.label);
}
for (int k=0; k < model.num_classes(); k++) {
probability_names.push_back(model.get_class_label(k));
}
List rs = List::create(results,probability_matrix,probability_names);
return rs;
}示例2: vd
void
viterbi(vector<Token> & vt, const ME_Model & me)
{
if (vt.size() == 0) return;
vector< vector<double> > mat;
vector< vector<int> > bpm;
vector<double> vd(me.num_classes());
for (size_t j = 0; j < vd.size(); j++) vd[j] = 0;
mat.push_back(vd);
for (size_t i = 0; i < vt.size(); i++) {
vector<double> vd(me.num_classes());
for (size_t j = 0; j < vd.size(); j++) vd[j] = -999999;
vector<int> bp(me.num_classes());
double maxl = -999999;
for (size_t j = 0; j < vd.size(); j++) {
if (mat[i][j] > maxl) maxl = mat[i][j];
}
for (size_t j = 0; j < vd.size(); j++) {
if (mat[i][j] < maxl - BEAM_WIDTH) continue; // beam thresholding
string prepos = me.get_class_label(j);
if (i == 0) {
if (j > 0) continue;
prepos = "BOS";
}
// prepos = me.get_class_name(j);
// if (i == 0 && prepos != "BOS") continue;
ME_Sample mes = mesample(vt, i, prepos);
vector<double> membp = me.classify(mes);
for (size_t k = 0; k < vd.size(); k++) {
double l = mat[i][j] + log(membp[k]);
if (l > vd[k]) {
bp[k] = j;
vd[k] = l;
}
}
}
mat.push_back(vd);
// for (int k = 0; k < vd.size(); k++) cout << bp[k] << " ";
// cout << endl;
bpm.push_back(bp);
}
/*
for (int i = 0; i < vt.size(); i++) {
int max_prd = 0;
for (int j = 0; j < vd.size(); j++) {
double l = mat[i+1][j];
if (l > mat[i+1][max_prd]) {
max_prd = j;
}
}
vt[i].prd = me.get_class_name(max_prd);
}
*/
// cout << "viterbi ";
int max_prd = 0;
int n = vt.size();
for (size_t j = 0; j < vd.size(); j++) {
double l = mat[n][j];
if (l > mat[n][max_prd]) {
max_prd = j;
}
}
vt[n-1].prd = me.get_class_label(max_prd);
for (int i = vt.size() - 2; i >= 0; i--) {
// cout << max_prd << " ";
// cerr << max_prd << " ";
if (max_prd < 0 || max_prd >= me.num_classes()) exit(0);
max_prd = bpm[i+1][max_prd];
vt[i].prd = me.get_class_label(max_prd);
}
// cout << endl;
}