SNN.Construction {HGC} | R Documentation

## Building Unweighted Shared Nearest Neighbor Graph

### Description

This function builds a Shared Nearest Neighbor (SNN) graph in the input feature space using Euclidean distance metric.

### Usage

    SNN.Construction(mat, k, threshold)

### Arguments

`mat` | the input data saved as a numerical matrix. The columns are the features and the rows are the samples.
`k` | the number of nearest neighbor number to build the original KNN.
`threshold` | the threshold parameter for the Jaccard index. The edges in KNN whose Jaccard indices are lower than it will be removed in building the SNN.

### Details

The function builds an SNN which saved as a sparse matrix.

### Value

An n by n binary dgCMatrix object C, where n is the number of input samples. The matrix C is the adjacency matrix of the built SNN graph. C[i,j] = 1 means that there is an edge between sample i and sample j.

### Examples

    data(Pollen)
    Pollen.PCs <- Pollen[["PCs"]]
    G <- SNN.Construction(Pollen.PCs)

[Package HGC version 1.0.3 Index]