predict.bagged.outliertrees: Predict method for Bagged OutlierTrees

In bagged.outliertrees: Robust Explainable Outlier Detection Based on OutlierTree

Description

Predict method for Bagged OutlierTrees

Usage

## S3 method for class 'bagged.outliertrees'
predict(
  object,
  newdata,
  min_outlier_score = 0.95,
  nthreads = parallel::detectCores(),
  ...
)

Arguments

object	A Bagged OutlierTrees object as returned by bagged.outliertrees.
newdata	A Data Frame in which to look for outliers according to the fitted model.
min_outlier_score	Minimum outlier score to use when finding outliers.
nthreads	Number of threads to use when predicting.
...	No use.

Value

Will return a list of lists with the outliers and their information (each row is an entry in the first list, with the same names as the rows in the input data frame), which can be printed into a human-readable format after-the-fact through functions print.

See Also

bagged.outliertrees print.bagged.outlieroutputs

Examples

library(bagged.outliertrees)

### example dataset with interesting outliers
data(hypothyroid)

### fit a Bagged OutlierTrees model
model <- bagged.outliertrees(hypothyroid,
  ntrees = 10,
  subsampling_rate = 0.5,
  z_outlier = 6,
  nthreads = 1
)

### use the fitted model to find outliers in the training dataset
outliers <- predict(model,
  newdata = hypothyroid,
  min_outlier_score = 0.5,
  nthreads = 1
)

### print the top-10 outliers in human-readable format
print(outliers, outliers_print = 10)

bagged.outliertrees documentation built on July 6, 2021, 9:06 a.m.