TestData


The data are generated according to the example in the paper "Kriegel, Kroger, Schubert, and Arthur Zimek, 2009, Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data".
The data has 60 rows and 3 variables. The first two variables are the x and y coordinates.
The third variable indicates the type of data, i.e., "Pattern_1", "Pattern_2", or "Outlier".
The first 25 observations belong to "Pattern_1". Another 25 observations represent "Pattern_2".
The other 10 observations are "Outliers".


datasets

Three high-dimensional outlier detection algorithms and a outlier unification scheme are implemented in this package. The angle-based outlier detection (ABOD) algorithm is based on the work of Kriegel, Schubert, and Zimek [2008]. The subspace outlier detection (SOD) algorithm is based on the work of Kriegel, Kroger, Schubert, and Zimek [2009]. The feature bagging-based outlier detection (FBOD) algorithm is based on the work of Lazarevic and Kumar [2005]. The outlier unification scheme is based on the work of Kriegel, Kroger, Schubert, and Zimek [2011].

Cheng Fan

HighDimOut

Outlier Detection Algorithms for High-Dimensional Data

TestData function

A data frame with 60 rows and 3 variables:

TestData: Testing data for testing the performance of different algorithms

Description

Usage

Arguments

Format

Examples