Description: In this paper, we present LOADED, an algorithm for outlier
detection in evolving data sets containing both continuous
and categorical attributes. LOADED is a tunable algorithm,
wherein one can trade off computation for accuracy so that
domain-specific response times are achieved. Experimental
results show that LOADED provides very good detection and
false positive rates, which are several times better than those
of existing distance-based schemes. Platform: |
Size: 192752 |
Author:甜甜 |
Hits:
Description: In this paper, we present LOADED, an algorithm for outlier
detection in evolving data sets containing both continuous
and categorical attributes. LOADED is a tunable algorithm,
wherein one can trade off computation for accuracy so that
domain-specific response times are achieved. Experimental
results show that LOADED provides very good detection and
false positive rates, which are several times better than those
of existing distance-based schemes. Platform: |
Size: 192512 |
Author:甜甜 |
Hits:
Description: // chebysheve outlier detection
// this function is used to detect the abnormal value among a set of data
// input:
// delta: a set of data
// flag: discribe which data is already known as outlier
// p: restrict level
// output:
// double[] door : byyond which the data may be considered as a outlier
// door[0]: the upperdoor
// door[1]: the lowerdoor Platform: |
Size: 1024 |
Author: |
Hits:
Description: 数据挖掘中的经典聚类算法，常用于异常值检测-Data Mining in a classic clustering algorithm, commonly used in the outlier detection Platform: |
Size: 246784 |
Author:jiangjinfeng |
Hits:
Description: 一个异常点是相当不同的或不符合一个数据集的其余部分数据。检测离群点是非常重要的许多应用中，并在最近引起了广泛关注 在数据挖掘研究界。在本文中，提出了一种方法检测发现异常数据的频繁模式（或频繁项目集-An outlier in a dataset is an observation or a point that is considerably
dissimilar to or inconsistent with the remainder of the data. Detection of
outliers is important for many applications and has recently attracted much attention
in the data mining research community. In this paper, we present a new
method to detect outliers by discovering frequent patterns (or frequent itemsets)
from the data set Platform: |
Size: 259072 |
Author:suivy |
Hits:
Search - Outlier Detection