28 KiB
SVM Classifier C++ 1.0.0
High-performance Support Vector Machine classifier with scikit-learn compatible API
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Abstract base class for multiclass classification strategies. More...
#include <multiclass_strategy.hpp>
Public Member Functions | |
virtual | ~MulticlassStrategyBase ()=default |
Virtual destructor. | |
virtual TrainingMetrics | fit (const torch::Tensor &X, const torch::Tensor &y, const KernelParameters ¶ms, DataConverter &converter)=0 |
Train the multiclass classifier. | |
virtual std::vector< int > | predict (const torch::Tensor &X, DataConverter &converter)=0 |
Predict class labels. | |
virtual std::vector< std::vector< double > > | predict_proba (const torch::Tensor &X, DataConverter &converter)=0 |
Predict class probabilities. | |
virtual std::vector< std::vector< double > > | decision_function (const torch::Tensor &X, DataConverter &converter)=0 |
Get decision function values. | |
virtual std::vector< int > | get_classes () const =0 |
Get unique class labels. | |
virtual bool | supports_probability () const =0 |
Check if the model supports probability prediction. | |
virtual int | get_n_classes () const =0 |
Get number of classes. | |
virtual MulticlassStrategy | get_strategy_type () const =0 |
Get strategy type. | |
Protected Attributes | |
std::vector< int > | classes_ |
Unique class labels. | |
bool | is_trained_ = false |
Whether the model is trained. | |
Detailed Description
Abstract base class for multiclass classification strategies.
Definition at line 20 of file multiclass_strategy.hpp.
Member Function Documentation
◆ decision_function()
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pure virtual |
Get decision function values.
- Parameters
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X Feature tensor of shape (n_samples, n_features) converter Data converter instance
- Returns
- Decision function values
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ fit()
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pure virtual |
Train the multiclass classifier.
- Parameters
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X Feature tensor of shape (n_samples, n_features) y Target tensor of shape (n_samples,) params Kernel parameters converter Data converter instance
- Returns
- Training metrics
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ get_classes()
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pure virtual |
Get unique class labels.
- Returns
- Vector of unique class labels
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ get_n_classes()
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pure virtual |
Get number of classes.
- Returns
- Number of classes
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ get_strategy_type()
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pure virtual |
Get strategy type.
- Returns
- Multiclass strategy type
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ predict()
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pure virtual |
Predict class labels.
- Parameters
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X Feature tensor of shape (n_samples, n_features) converter Data converter instance
- Returns
- Predicted class labels
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ predict_proba()
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pure virtual |
Predict class probabilities.
- Parameters
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X Feature tensor of shape (n_samples, n_features) converter Data converter instance
- Returns
- Class probabilities for each sample
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
◆ supports_probability()
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pure virtual |
Check if the model supports probability prediction.
- Returns
- True if probabilities are supported
Implemented in svm_classifier::OneVsRestStrategy, and svm_classifier::OneVsOneStrategy.
Member Data Documentation
◆ classes_
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protected |
Unique class labels.
Definition at line 92 of file multiclass_strategy.hpp.
◆ is_trained_
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protected |
Whether the model is trained.
Definition at line 93 of file multiclass_strategy.hpp.
The documentation for this class was generated from the following file:
- include/svm_classifier/multiclass_strategy.hpp
Generated on Sun Jun 22 2025 11:25:27 for SVM Classifier C++ by