The increased nature of email spam with the use of urge mailing tools prompt the need for detector generation to counter the menace of unsolocited email. Detector generation inspired by the human immune system implements particle swarm optimization (PSO) to generate detector in negative selection algorithm (NSA). Outlier detectors are unique features generated by local outlier factor (LOF). The...

the objective of this research was to discriminate four local breeds of goat in central java-indonesia using multivariate analysis. data from eight morphological traits of four goat breeds, namely kejobong goat (jg), etawa grade goat (egg), kacang goat (kg) and jawarandu goat (rg) originated from purbalingga, purworejo, grobogan and pemalang regencies, respectively, were used. one hundred and s...

We present a novel resolution-based outlier notion and a nonparametric outlier-mining algorithm, which can efficiently identify top listed outliers from a wide variety of datasets. The algorithm generates reasonable outlier results by taking both local and global features of a dataset into consideration. Experiments are conducted using both synthetic datasets and a real life construction equipm...

In an industrial context, the activity of sensors is recorded at a high frequency. A challenge to automatically detect abnormal measurement behavior. Considering sensor measures as functional data, problem can be formulated detection outliers in multivariate data set. Due heterogeneity this set, proposed contaminated mixture model both clusters into homogeneous groups and detects outliers. The ...

This work presents an adaptive outlier detection technique for data streams, called Automatic Outlier Detection for Data Streams (A-ODDS), which identifies outliers with respect to all the received data points (global context) as well as temporally close data points (local context) where local context are selected based on time and change of data distribution.

Multivariate outlier detection based on the Mahalanobis distance with the BACON-EEM algorithm, the TRC algorithm and the ER algorithm is presented and imputation of outliers and further missing values is discussed. The methods are illustrated with a data set on Swedish municipalities. The relation between outliers, influential observations and selective editing is explored. Finally robust multi...

The aim of detecting outliers in a multivariate sample can be pursued in diierent ways. We investigate here the performance of several simultaneous multivariate outlier identiication rules based on robust estimators of location and scale. It has been shown that the use of estimators with high nite-sample breakdown point in such procedures yields a good behaviour with respect to the prevention o...