Search for outliers in abnormal data 1 Introduction

The outliers are then removed and further training is performed using a reduced pattern size.







Outliers Detection Based on Buantiles and Depth Functions
Outlier detection: The aim of this course is to introduce the basic concepts and usefulness of outlier analysis. Indeed, outliers may be a nuisance for a given ...
Outlier detection and Extreme values theory
In our work, we follow two of the commonly-used definitions: Distance-based outliers [28]: A point p in a dataset T is a (D, r)-outlier if at most D of the ...
Online Outlier Detection in Sensor Data Using Non-Parametric Models
Outliers, as defined earlier, are patterns in data that do not conform to a well defined notion of normal behavior, or conform to a well defined notion of ...
Outlier Detection : A Survey
An outlier is an observation with a value that does not appear to belong with the rest of the values in the data set. Outliers are also known by other names: ...
Dealing with Outliers
There are two types of outliers in functional data analysis: magnitude outliers and shape outliers. In general, magnitude outliers appear far apart from other ...
Outlier detection based on the functional coefficient of variation
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Tutorials (?TD?) are with exercises on paper and on computer. Each student must load on his personal computer, before the course, a programming environment ...
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Results of Open Testing for the Program to Assess the Reliability of ...
Cet ouvrage présente les travaux du groupe d'experts réunis par l'Inserm dans le cadre de la procédure d'expertise collective, pour répondre ...