ldf: LDF Outlier score calculation
In lenaWitterauf/rElki: An R interface to Java package ELKI (Version 0.7.5)

Description Usage Arguments Value See Also Examples

ldf returns the LDF Outlier score for every observation in the given data_matrix. Kernel density estimation in combination with the reachability concept of LOF is used to calculate outlier score.

1	ldf(data_matrix, k, h = 1, c = 0.1)

`data_matrix`	numeric Matrix containing data the outlier score is calculated for. Rows are treated as observations, columns as features.
`k`	Number. Neighbourhood-size used to calculate outlier scores.
`h`	Number. Bandwidth scaling factor. Defaults to ELKI's default (1).
`c`	Number. Scaling constant to limit value range to 1/c. Defaults to ELKI's default (0.1).

List of outlier scores. The score at position x belongs to the observation given in row x of the original data_matrix.

https://elki-project.github.io/releases/release0.7.5/javadoc/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/LDF.html for ELKI documentation.

data_matrix <- matrix(c(1:30), nrow=10, ncol=3)
result      <- ldf(data_matrix, 3)
for(index in c(1:10)) {
    print(paste('Observation:', paste(data_matrix[index,], collapse=',')))
    print(paste('Score:',       result[index]))
}