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PLSSVM - Parallel Least Squares Support Vector Machine
2.0.0
A Least Squares Support Vector Machine implementation using different backends.
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Implements a data set class encapsulating all data points, features, and potential labels. More...
#include "plssvm/detail/io/arff_parsing.hpp"#include "plssvm/detail/io/file_reader.hpp"#include "plssvm/detail/io/libsvm_parsing.hpp"#include "plssvm/detail/io/scaling_factors_parsing.hpp"#include "plssvm/detail/logger.hpp"#include "plssvm/detail/performance_tracker.hpp"#include "plssvm/detail/string_utility.hpp"#include "plssvm/detail/type_list.hpp"#include "plssvm/detail/utility.hpp"#include "plssvm/exceptions/exceptions.hpp"#include "plssvm/file_format_types.hpp"#include "fmt/chrono.h"#include "fmt/core.h"#include "fmt/ostream.h"#include <algorithm>#include <chrono>#include <cstddef>#include <functional>#include <iostream>#include <limits>#include <map>#include <memory>#include <optional>#include <set>#include <string>#include <tuple>#include <utility>#include <vector>Go to the source code of this file.
Classes | |
| class | plssvm::data_set< T, U > |
| Encapsulate all necessary data that is needed for training or predicting using an SVM. More... | |
| class | plssvm::data_set< T, U >::scaling |
| Implements all necessary data and functions needed for scaling a plssvm::data_set to an user-defined range. More... | |
| struct | plssvm::data_set< T, U >::scaling::factors |
| The calculated or read feature-wise scaling factors. More... | |
| class | plssvm::data_set< T, U >::label_mapper |
| Implements all necessary functionality to map arbitrary labels to labels usable by the C-SVMs. More... | |
Namespaces | |
| plssvm | |
| The main namespace containing all public API functions. | |
Typedefs | |
| template<typename T > | |
| using | plssvm::optional_ref = std::optional< std::reference_wrapper< T > > |
Type alias for an optional reference (since std::optional<T&> is not allowed). More... | |
Implements a data set class encapsulating all data points, features, and potential labels.