The "absolutely attribute distance" is defined,after that,it solves the problems which CABOSFV can t solve,and according to the false outliers often happen after clustering,the paper gives some strategies to get better outlier data.

Outlier Mining Model Based on ICA and MViSOM;

An Algorithm of Edge Extraction of Color Face Based on Outlier Detection;

Outlier Mining Model Based on ICA & SVM;

The residue calculation problem of a function at an isolated singularity is discussed and two improved computational formulas are given in this paper.

A new algorithm on clustering analysis is put forward,by which the problem of clustering and the examination of the isolated point at the same time can be solved.

We used colour images of whitefly as samples,studied and discussed isolated point and unrelated small areas after performing gray level process and binary proces

Application of an improved k-means algorithm based on outliers and original clustering center

Not only is it sensitive to the order of sample data,but also it may make out the local excellent and be affected by the outliers.

ODRKNN counts the number of each point s reverse K nearest neighbors to reflect its isolation degree,experimental results on synthesized and real world dataset show that ODRKNN can efficiently detect outliers and has higher efficiency than outliers detection algorithm LOF and LSC.