| NetDA-package {NetDA} | R Documentation |
Network-Based Discriminant Analysis Subject to Multi-Label Classes
Description
Implementation of discriminant analysis with network structures in predictors accommodated to do classification and prediction.
Details
There are two functions in this package: NetDA and Metrics. NetDA aims to construct network-based linear discriminant function and network-based quadratic discriminant function based on the training data, and then do classification for individuals in the testing data. Predicted values can be determined by NetDA. The function Metrics provides a confusion matrix and some commonly used criteria to assess the performance of classification and prediction.
Author(s)
Chen, L.-P.
Maintainer: Li-Pang Chen <lchen723@nccu.edu.tw>
References
Chen, L.-P. (2022) Network-Based Discriminant Analysis for Multiclassification. Under revision.
Friedman, J., Hastie, T., and Tibshirani, R. (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9, 432-441.