PLSSVM - Parallel Least Squares Support Vector Machine
2.0.0
A Least Squares Support Vector Machine implementation using different backends.
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Defines the functions used for prediction for the C-SVM using the CUDA backend. More...
#include "plssvm/constants.hpp"
Namespaces | |
plssvm | |
The main namespace containing all public API functions. | |
plssvm::cuda | |
Namespace containing the C-SVM using the CUDA backend. | |
Functions | |
template<typename real_type > | |
__global__ void | plssvm::cuda::device_kernel_w_linear (real_type *w_d, const real_type *data_d, const real_type *data_last_d, const real_type *alpha_d, const kernel_index_type num_data_points, const kernel_index_type num_features) |
Calculate the w vector to speed up the prediction of the labels for data points using the linear kernel function. More... | |
template<typename real_type > | |
__global__ void | plssvm::cuda::device_kernel_predict_polynomial (real_type *out_d, const real_type *data_d, const real_type *data_last_d, const real_type *alpha_d, const kernel_index_type num_data_points, const real_type *points, const kernel_index_type num_predict_points, const kernel_index_type num_features, const int degree, const real_type gamma, const real_type coef0) |
Predicts the labels for data points using the polynomial kernel function. More... | |
template<typename real_type > | |
__global__ void | plssvm::cuda::device_kernel_predict_rbf (real_type *out_d, const real_type *data_d, const real_type *data_last_d, const real_type *alpha_d, const kernel_index_type num_data_points, const real_type *points, const kernel_index_type num_predict_points, const kernel_index_type num_features, const real_type gamma) |
Predicts the labels for data points using the radial basis functions kernel function. More... | |
Defines the functions used for prediction for the C-SVM using the CUDA backend.