RNN.Construction {HGC} | R Documentation

## Building Unweighted ε Nearest Neighbor Graph

### Description

This function builds an ε Nearest Neighbor graph in the input feature space using Euclidean distance metric.

### Usage

    RNN.Construction(mat, max_dist)

### Arguments

`mat` | the input data saved as a numerical matrix. The columns are the features and the rows are the samples.
`max_dist` | the threshold distance. The edges whose lengths are less than `max_dist` will be kept in the graph.

### Details

The function builds an ε Nearest Neighbor graph 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 RNN 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 <- RNN.Construction(Pollen.PCs, 20)

[Package HGC version 1.2.0 Index]