Man pages for spectralGraphTopology
Learning Graphs from Data via Spectral Constraints
| A | Computes the Adjacency linear operator which maps a vector of... |
| accuracy | Computes the accuracy between two matrices |
| Astar | Computes the Astar operator. |
| block_diag | Constructs a block diagonal matrix from a list of square... |
| cluster_k_component_graph | Cluster a k-component graph from data using the Constrained... |
| D | Computes the degree operator from the vector of edge weights. |
| Dstar | Computes the Dstar operator, i.e., the adjoint of the D... |
| fdr | Computes the false discovery rate between two matrices |
| fscore | Computes the fscore between two matrices |
| L | Computes the Laplacian linear operator which maps a vector of... |
| learn_bipartite_graph | Learn a bipartite graph Learns a bipartite graph on the basis... |
| learn_bipartite_k_component_graph | Learns a bipartite k-component graph Jointly learns the... |
| learn_combinatorial_graph_laplacian | Learn the Combinatorial Graph Laplacian from data Learns a... |
| learn_graph_sigrep | Learn graphs from a smooth signal representation approach... |
| learn_k_component_graph | Learn the Laplacian matrix of a k-component graph Learns a... |
| learn_laplacian_gle_admm | Learn the weighted Laplacian matrix of a graph using the ADMM... |
| learn_laplacian_gle_mm | Learn the weighted Laplacian matrix of a graph using the MM... |
| learn_smooth_approx_graph | Learns a smooth approximated graph from an observed data... |
| learn_smooth_graph | Learn a graph from smooth signals This function learns a... |
| Lstar | Computes the Lstar operator. |
| npv | Computes the negative predictive value between two matrices |
| recall | Computes the recall between two matrices |
| relative_error | Computes the relative error between the true and estimated... |
| specificity | Computes the specificity between two matrices |
| spectralGraphTopology-package | Package spectralGraphTopology |
