Density Convoluted Support Vector Machines
Compute Coefficients from a "cv.dcsvm" Object
Compute Coefficients for Sparse Density-Convoluted SVM
Cross-Validation for Sparse Density-Convoluted SVM
Internal DCSVM Functions
Density-Convoluted Support Vector Machines
Density-Convoluted Support Vector Machine
Plot the Cross-Validation Curve of Sparse Density-Convoluted SVM
Plot Coefficients for Sparse Density-Convoluted SVM
Make Predictions from a "cv.dcsvm" Object
Make Predictions for Sparse Density-Convoluted SVM
Print a DCSVM Object
Implements an efficient algorithm for solving sparse-penalized support vector machines with kernel density convolution. This package is designed for high-dimensional classification tasks, supporting lasso (L1) and elastic-net penalties for sparse feature selection and providing options for tuning kernel bandwidth and penalty weights. The 'dcsvm' is applicable to fields such as bioinformatics, image analysis, and text classification, where high-dimensional data commonly arise. Learn more about the methodology and algorithm at Wang, Zhou, Gu, and Zou (2023) <doi:10.1109/TIT.2022.3222767>.