Safe Haskell | None |
---|---|

Language | Haskell2010 |

## Synopsis

- spectralClusterKNorm :: Int -> Int -> AdjacencyMatrix -> LabelVector
- spectralClusterNorm :: AdjacencyMatrix -> LabelVector
- spectralNorm :: Int -> Int -> AdjacencyMatrix -> [Vector Double]
- getDegreeMatrix :: AdjacencyMatrix -> Matrix Double
- type AdjacencyMatrix = Matrix Double

# Documentation

spectralClusterKNorm :: Int -> Int -> AdjacencyMatrix -> LabelVector Source #

Returns the clustering of eigenvectors with the second smallest eigenvalues and on of the symmetric normalized Laplacian L. Computes real symmetric part of L, so ensure the input is real and symmetric. Diagonal should be 0s for adjacency matrix. Clusters the eigenvector using kmeans into k groups from e eigenvectors.

spectralClusterNorm :: AdjacencyMatrix -> LabelVector Source #

Returns the eigenvector with the second smallest eigenvalue of the symmetric normalized Laplacian L. Computes real symmetric part of L, so ensure the input is real and symmetric. Diagonal should be 0s for adjacency matrix.

spectralNorm :: Int -> Int -> AdjacencyMatrix -> [Vector Double] Source #

Returns the eigenvectors with the Nth smallest eigenvalue and on of the symmetric normalized Laplacian L. Computes real symmetric part of L, so ensure the input is real and symmetric. Diagonal should be 0s for adjacency matrix.

getDegreeMatrix :: AdjacencyMatrix -> Matrix Double Source #

Obtain the degree matrix.

type AdjacencyMatrix = Matrix Double Source #