58 citations · 312 across the 28 of their papers we have counts for
8 papers · 1 filter
K-ANMI: A Mutual Information Based Clustering Algorithm for Categorical Data
Zengyou He, Xiaofei Xu, Shengchun Deng
Clustering categorical data is an integral part of data mining and has attracted much attention recently. In this paper, we present k-ANMI, a new efficient algorithm for clustering…
K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset
Zengyou He, Xiaofei Xu, Shengchun Deng +1
Clustering categorical data is an integral part of data mining and has attracted much attention recently. In this paper, we present k-histogram, a new efficient algorithm for clust…
Clustering Mixed Numeric and Categorical Data: A Cluster Ensemble Approach
Zengyou He, Xiaofei Xu, Shengchun Deng
Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datase…
A Fast Greedy Algorithm for Outlier Mining
Zengyou He, Xiaofei Xu, Shengchun Deng
The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. In [38], the problem of outlier detection i…
A Unified Subspace Outlier Ensemble Framework for Outlier Detection in High Dimensional Spaces
Zengyou He, Xiaofei Xu, Shengchun Deng
The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such outliers is important for…
An Optimization Model for Outlier Detection in Categorical Data
Zengyou He, Xiaofei Xu, Shengchun Deng
The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such outliers is important for…