odetector (version 1.0.1)

remove.outliers: Remove outliers

Description

Removes the detected outliers from a data set.

Usage

remove.outliers(x, ot=1, sc=FALSE)

Value

Xr

a numeric matrix containing the outliers-removed data set.

Arguments

x

an object of outliers class containing the outliers to be removed.

ot

an integer specifying the outlier detection approach. The default is 1 for the Approach 1. For the other methods use 2 or 3. See detect.outliers for the details.

sc

a logical value for including the objects in the small clusters into removal process. The default is FALSE. Use TRUE for removing the objects in the small clusters.

Author

Zeynel Cebeci, Cagatay Cebeci, Yalcin Tahtali

See Also

detect.outliers, pairs.outliers, plot.outliers, print.outliers, summary.outliers

Examples

# Load the dataset x3p4c and extract the first three columns to x
data(x3p4c)
x <- x3p4c[,1:3]

# For 4 clusters, run Unsupervised Possibilistic Fuzzy C-Means (UPFC) algorithm 
# of the package ppclust 
res.upfc <- ppclust::upfc(x, centers=4)

# Detect the outliers 
out <- detect.outliers(res.upfc)
 
# Remove the outliers 
Xr1 <- remove.outliers(out, ot=1)
print(Xr1)

# Remove the outliers including the collective outliers 
Xr2 <- remove.outliers(out, ot=1, sc=TRUE)
print(Xr2)