outlier

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outlier

[′au̇t‚lī·ər]
(geology)
A group of rocks separated from the main mass and surrounded by outcrops of older rocks.
(statistics)
In a set of data, a value so far removed from other values in the distribution that its presence cannot be attributed to the random combination of chance causes.

outlier

An entity outside the norm. Pronounced "out-liar," an outlier may refer to a person, organization or to data way outside the normal range. See anomaly detection.
References in periodicals archive ?
Once identified, the origins of the outliers can be determined.
When a workforce sees that there is consistency in the way they are treated, the fact that some attention needs to be paid to outlier employees is far more readily understood.
"Outliers" is implicitly feminist, featuring many women as well as artists, like Greer Lankton, whose gender, like their art, falls "outside" binary logics.
Let us turn now to breaks-in-mean-adjusted series; in order to adjust GDP growth series for breaks in mean, we incorporate the various types of outliers based on dummy variables that take a value of one from each point of structural break onwards and take a value of zero elsewhere.
The biggest risk to the status quo is the outlier. Challenges to existing research and research biases work best when outliers break the mold and advance into fresh territory, which is often less tainted with the entrenched problems of traditional scholarship.
Then the k value for the normal data type, from which the outliers were removed, are recalculated and again the LOF algorithm is applied.
From a practical point of view, it is well known that Pearson's correlation is not resistant to outliers and thus choosing weights in (2) based on this correlation will cause uncertain and deceptive results.
In this section, we introduce our online gradient learning method, which is called RoAdam (Robust Adam) to train long short-term memory (LSTM) for time series prediction in the presence of outliers. Our method does not directly detect the outliers and adaptively tunes the learning rate when facing a suspicious outlier.
Then delete the observations in the dependent variable related to the outliers to obtain [Y.sub.b] (free from outliers).
For a comparison with the percentile method described above, we investigate other common methods to identify outliers:
To determine point outliers, outlier detection is conducted using the standard deviation method.
Unlike other outlier detect method (such as the traditional AR model detection method), the outliers detect method proposed in this paper does not need to set the detection threshold.