// Copyright (C) 2018 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#undef DLIB_AUTO_LEARnING_ABSTRACT_Hh_
#ifdef DLIB_AUTO_LEARnING_ABSTRACT_Hh_
#include "kernel_abstract.h"
#include "function_abstract.h"
#include <chrono>
#include <vector>
namespace dlib
{
normalized_function<decision_function<radial_basis_kernel<matrix<double,0,1>>>> auto_train_rbf_classifier (
std::vector<matrix<double,0,1>> x,
std::vector<double> y,
const std::chrono::nanoseconds max_runtime,
bool be_verbose = true
);
/*!
requires
- is_binary_classification_problem(x,y) == true
- y contains at least 6 examples of each class.
ensures
- This routine trains a radial basis function SVM on the given binary
classification training data. It uses the svm_c_trainer to do this. It also
uses find_max_global() and 6-fold cross-validation to automatically determine
the best settings of the SVM's hyper parameters.
- The hyperparameter search will run for about max_runtime and will print
messages to the screen as it runs if be_verbose==true.
!*/
}
#endif // DLIB_AUTO_LEARnING_ABSTRACT_Hh_