R: Breakdown for Mahalanobis Distance

bd_row {anomalyDetection} | R Documentation

## Breakdown for Mahalanobis Distance

### Description

`bd_row` indicates which variables in data are driving the Mahalanobis distance for a specific row `r`, relative to the mean vector of the data.

### Usage

    bd_row(data, row, n = NULL)

### Arguments

`data` | numeric data
`row` | row of interest
`n` | number of values to return. By default, will return all variables (columns) with their respective differences. However, you can choose to view only the top `n` variables by setting the `n` value.

### Value

Returns a vector indicating the variables in `data` that are driving the Mahalanobis distance for the respective row.

### See Also

`mahalanobis_distance` for computing the Mahalanobis Distance values

### Examples

    ## Not run:
    x = matrix(rnorm(200*3), ncol = 10)
    colnames(x) = paste0("C", 1:ncol(x))

    # compute the relative differences for row 5 and return all variables
    x %>%
      mahalanobis_distance("bd", normalize = TRUE) %>%
      bd_row(5)

    # compute the relative differences for row 5 and return the top 3 variables
    # that are influencing the Mahalanobis Distance the most
    x %>%
      mahalanobis_distance("bd", normalize = TRUE) %>%
      bd_row(5, 3)

    ## End(Not run)

[Package anomalyDetection version 0.2.5 Index]