36template<CV_STRAT cv_strat>
40 std::size_t min_size_ts =
static_cast<std::size_t
>(min_dim_ts);
41 std::size_t max_size_ts =
static_cast<std::size_t
>(max_dim_ts);
45 m_strategy.reserve(max_size_ts - min_size_ts);
47 for(std::size_t i = min_size_ts; i < max_size_ts; ++i)
50 std::vector<int> train_set;
52 train_set.emplace_back(i);
55 std::vector<int> validation_set;
56 validation_set.reserve(1);
57 validation_set.emplace_back(i);
59 m_strategy.emplace_back(std::make_pair(train_set,validation_set));
72template<CV_STRAT cv_strat>
77 return std::make_pair( data.leftCols(strat.first.front()), data.col(strat.second.front()) );
Contains the class for creating the split training/validation set.
std::pair< std::vector< int >, std::vector< int > > iter_cv_t
Definition strategy_cv.hpp:62
std::pair< KO_Traits::StoringMatrix, KO_Traits::StoringMatrix > train_valid_set_t
Definition strategy_cv.hpp:66
std::integral_constant< CV_STRAT, cv_strat > CV_STRAT_T
Definition strategy_cv.hpp:52
Eigen::MatrixXd StoringMatrix
Matrix data structure.
Definition traits_ko.hpp:49