We have proposed replicator neural networks (RNNs) as an outlier detecting algorithm [15]. Here we compare RNN for outlier detection with three other methods using both publicly a...
Graham J. Williams, Rohan A. Baxter, Hongxing He, ...
In this paper we present a novel Incremental Hierarchical Clustering (IHC) algorithm. Our approach aims to construct a hierarchy that satisfies the homogeneity and the monotonici...
One of the problems with existing clustering methods is that the interpretation of clusters may be difficult. Two different approaches have been used to solve this problem: conce...
Temporal data mining aims at finding patterns in historical data. Our work proposes an approach to extract temporal patterns from data to predict the occurrence of target events,...
Segmentation is a popular technique for discovering structure in time series data. We address the largely open problem of estimating the number of segments that can be reliably di...
Association rule mining is an important data mining problem. It is found to be useful for conventional relational data. However, previous work has mostly targeted on mining a sing...
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...