Примеры использования Outlier на Английском языке и их переводы на Русский язык
{-}
-
Official
-
Colloquial
Transactions Outlier analyzes.
It is a clear statistical outlier.
Outlier review: C1-Money and C4-CPHO claims.
Explanation and review of outlier claims.
Outlier analysis should take into account two different kinds of outliers. .
That is a point which is too far from its closest seed can be treated as an outlier.
There is only one outlier LC50=470 mg/L after 48 h for Leuciscus idus melonatus.
Similarities result in clusters andpatterns while differences show unique or outlier events.
Delete the Last Impact(Outlier) Obvious outliers may deleted if desired.
Outlier Treatment(attribute outliers): defines the outlier treatment to be use.
Subspace-, correlation-based and tensor-based outlier detection for high-dimensional data.
Thus, outlier claims are also included in the application phases of the respective models.
Adding any of them should make the youthful candidate the outlier and you the victor via asymmetrical dominance.
Outlier detection of multivariate extrapolated administrative data in belgian national accounts.
The United Kingdom suggested that simpler methods for outlier treatments may work just as well.
A value of 1 or even less indicates a clear inlier, butthere is no clear rule for when a point is an outlier.
The Mahalanobis-distance of the(fictional) outlier at(7,5;8,5)- meaning that P2 is 10 times higher than P1- equals 7,12.
Such outlier claims that had been removed from earlier processing cycles were subsequently reviewed and, where appropriate, amended.
Beshtau is an isolated five-domed mountain- laccoliths,the highest of 17 outlier igneous mountains of Pyatigorje in the Caucasian Mineral Waters.
Invited paper 8: Outlier detection of multivariate extrapolated administrative data in Belgian national accounts.
In the Indian pharmaceutical industry,recognised for its prowess in generic pharmaceuticals, Troikaa is an outlier.
The ultimate aim of an outlier detection system is to single out suspicious observations so that they can be inspected manually.
Key words: sample, binary sequence, data processing, filtering, exploratory analysis,stationarity of sample values, outlier analysis, statistical criteria.
For example, a point at a"small" distance to a very dense cluster is an outlier, while a point within a sparse cluster might exhibit similar distances to its neighbors.
Because extrapolating data always carries some risk of erroneous extrapolation,a robust and preferably automated outlier detection system is needed.
To test whether the minimum value is an outlier, the test statistic is G Y¯- Y min s{\displaystyle G={\frac{{\bar{Y}}-Y_{\min}}{s}}} with Ymin denoting the minimum value.
Supervised anomaly detection techniques require a data set that has been labeled as"normal" and"abnormal" andinvolves training a classifier the key difference to many other statistical classification problems is the inherent unbalanced nature of outlier detection.
The monument covers an area of about 36.7 hectares and includes the outlier"Four brothers" and other small outliers within a radius of 250 meters.
The presumption that the outlier is wrong until proven correct was modified- scrutineers now adopt the approach of revalidating a price quote initially identified as an outlier unless evidence already exists to the contrary.
There exist extensionsof LOF that try to improve over LOF in these aspects: Feature Bagging for Outlier Detection runs LOF on multiple projections and combines the results for improved detection qualities in high dimensions.