C++ (Cpp) eigen_wsvec_list_t Examples

Example #1

File: eigen_feature_mapper.cpp Project: AutonomicSecurity/jubatus

wplist eigen_feature_mapper::revert(
    const eigen_wsvec_list_t& src) const {
  wplist ret(src.size());
  eigen_wsvec_list_t::const_iterator ib = src.begin();
  wplist::iterator ob = ret.begin();
  while (ib != src.end()) {
    *ob = revert(*ib);
    ++ob;
    ++ib;
  }
  return ret;
}

Example #2

File: gmm.cpp Project: gintenlabo/jubatus_core

void gmm::batch(const eigen_wsvec_list_t& data, int d, int k) {
  if (data.empty()) {
    *this = gmm();
    return;
  }

  typedef eigen_wsvec_list_t::const_iterator data_iter;
  initialize(data, d, k);

  eigen_svec_list_t old_means;
  eigen_smat_list_t old_covs;
  eigen_solver_list_t old_solvers;
  double old_obj = 0, obj = 0;
  vector<double> weights(k);

  bool converged = false;
  int64_t niter = 1;
  while (!converged) {
    old_covs = covs_;
    old_means = means_;
    old_solvers = cov_solvers_;
    old_obj = obj;
    obj = 0;
    fill(weights.begin(), weights.end(), 0);
    fill(means_.begin(), means_.end(), eigen_svec_t(d));
    fill(covs_.begin(), covs_.end(), eigen_smat_t(d, d));

    for (data_iter i = data.begin(); i != data.end(); ++i) {
      eigen_svec_t cps =
          cluster_probs(i->data, old_means, old_covs, old_solvers);
      for (int c = 0; c < k; ++c) {
        double cp = i->weight * cps.coeff(c);
        means_[c] += cp * i->data;
        covs_[c] += i->data * (i->data.transpose()) * cp;
        weights[c] += cp;
        obj -= std::log(std::max(cp, std::numeric_limits<double>::min()));
      }
    }
    for (int c = 0; c < k; ++c) {
      means_[c] /= weights[c];
      covs_[c] /= weights[c];
      double eps = 0.1;
      covs_[c] -= means_[c] * means_[c].transpose();
      covs_[c] += eps * eye_;
      cov_solvers_[c] =
          shared_ptr<eigen_solver_t>(new eigen_solver_t(covs_[c]));
    }
    converged = is_converged(niter++, means_, old_means, obj, old_obj);
  }
}

Example #3

File: gmm.cpp Project: gintenlabo/jubatus_core

void gmm::initialize(const eigen_wsvec_list_t& data, int d, int k) {
  d_ = d;
  k_ = k;
  means_ = eigen_svec_list_t(k);
  covs_ = eigen_smat_list_t(k, eigen_smat_t(d, d));
  cov_solvers_ = eigen_solver_list_t(k);
  eye_ = eigen_smat_t(d, d);

  for (int i = 0; i < d; ++i) {
    eye_.insert(i, i) = 1;
  }

  jubatus::util::math::random::mtrand r(time(NULL));
  for (int c = 0; c < k; ++c) {
    means_[c] = data[r.next_int(0, data.size()-1)].data;
    for (int i = 0; i < d; ++i) {
      covs_[c].insert(i, i) = 1;
    }
    cov_solvers_[c] = shared_ptr<eigen_solver_t>(new eigen_solver_t(covs_[c]));
  }
}