DBSCAN_method: DBSCAN_method

In OutliersLearn: Educational Outlier Package with Common Outlier Detection Algorithms

DBSCAN_method

Description

Outlier detection method using DBSCAN

Usage

DBSCAN_method(inputData, max_distance_threshold, min_pts, tutorialMode)

Arguments

inputData	Input Data (must be a data.frame)
max_distance_threshold	This is used to calculate the distance between all the points and check if the euclidean distance is less than the max_distance_threshold parameter to decide if add it to the neighbors or not
min_pts	the minimum number of points to form a dense region
tutorialMode	if TRUE the tutorial mode is activated (the algorithm will include an explanation detailing the theory behind the outlier detection algorithm and a step by step explanation of how is the data processed to obtain the outliers following the theory mentioned earlier)

Value

None, does not return any value

Author(s)

Andres Missiego Manjon

Examples

inputData = t(matrix(c(3,2,3.5,12,4.7,4.1,5.2,
4.9,7.1,6.1,6.2,5.2,14,5.3),2,7,dimnames=list(c("r","d"))));
inputData = data.frame(inputData);
eps = 4;
min_pts = 3;
DBSCAN_method(inputData, eps, min_pts, FALSE); #Can be set to TRUE

OutliersLearn documentation built on June 22, 2024, 10:23 a.m.