Sentence examples for outlier detection techniques from inspiring English sources

Outlier detection techniques can be categorized, based on the number of variables or dimensions used to define the outliers, into two categories; univariate outlier detection techniques; where the outliers are detected for only one variable at a time, and the other category is the multivariate outlier detection where more than one variable is taken into account while defining the outliers.

By using the above two outlier detection techniques to calculate the degree of outlierness of each object, our algorithms can guarantee that the chosen initial cluster centers are not outliers.

Although study on outlier detection techniques has long been an area of much research, few of those works relate to an Internet of Things (IoT) environment.

In this paper, we take into account the correlation between sensor data attributes and propose two distributed and online outlier detection techniques based on a hyperellipsoidal one-class support vector machine (SVM).

A variety of outlier detection techniques have been developed in several research communities.

For a good survey on outlier detection techniques for WSNs, see [23].

In addition, an outlier detection technique has been applied for identifying irregular behaviors inside each of the considered classes.

Moreover, we adopt an outlier detection technique to filter the extreme price from the series.

Datasets 1 and 4 were reprocessed using an outlier detection technique (see Methods).

An effective and efficient outlier detection technique for WSNs not only identifies outliers in a distributed and online manner with high detection accuracy and low false alarm, but also satisfies WSN constraints in terms of communication, computational and memory complexity.

Later, we show the great potentials of the outlier edge detection technique in the areas of graph mining and pattern recognition.