KNN.Construction {HGC} | R Documentation

## Building Unweighted K Nearest Neighbor Graph

### Description

This function builds an Unweighted K Nearest Neighbor (KNN) graph in the input feature space using Euclidean distance metric.

### Usage

    KNN.Construction(mat, k)

### 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 neighbors for building the KNN graph.

### Details

This function builds a KNN graph of the input data. The main function comes from the R package `RANN`.

### 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 KNN 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 <- KNN.Construction(Pollen.PCs)

[Package HGC version 1.0.3 Index]