R: Assigning New Points to a Clustering

predict {dbscan} | R Documentation

## Assigning New Points to a Clustering

### Description

Predict the membership of a new point given a clustering.

### Usage

    ## S3 method for class 'dbscan_fast'
    predict(object, newdata, data, ...)

    ## S3 method for class 'optics'
    predict(object, newdata, data, ...)

    ## S3 method for class 'hdbscan'
    predict(object, newdata, data, ...)

### Arguments

`object` | clustering object.
`newdata` | new data points for which the cluster membership should be predicted.
`data` | the data set used to create the clustering object.
`...` | further arguments.

### Details

For DBSCAN: If a new point is in the eps neighborhood of a point in the clustering, the the label of that point is predicted, otherwise the prediction is `0` (noise).

For OPTICS: Extracts a DBSCAN clustering and use predict for DBSCAN.

For HDBSCAN: Find the k-nearest neighbors with the smallest mutual reachability distance to predict the label

### See Also

Other clustering functions: `dbscan()`, `extractFOSC()`, `hdbscan()`, `jpclust()`, `optics()`, `sNNclust()`

[Package dbscan version 1.1-9 Index]