Add to ORKGNational audienceIn this paper we consider different entropy-based approaches to Pattern Mining. We discuss how entropy on pattern sets can be defined and how it can be incorporated into different stages of mining, from computing candidates to interesting patterns to assessing quality of pattern sets
AbstractThis paper describes the outlier data mining and commonly used outlier mining methods, on th...
International audienceKöpf and Basin have discussed the relation between brute-force guessing attack...
Recent research has highlighted the practical benefits of subjective interestingness measures, which...
The discovery of patterns plays an important role in data mining. A pattern can be any type of regul...
In this thesis, we study objective interesting pattern mining processes on datasets such as used in ...
The idea of frequent pattern discovery is to find frequently occurring events in large databases. Su...
Many algorithms of machine learning use an entropy measure as optimization criterion. Among the wide...
Abstract. In exploratory data mining it is important to assess the significance of results. Given th...
International audienceEntropic measures such as conditional entropy or mutual information have been ...
Entropy is a central concept in physics and has deep connections with Information theory, which is o...
In the machine learning literature we can find numerous methods to solve classification problems. We...
Pattern Mining is one of the most researched topics in the data mining community. Literally hundreds...
Abstract — In this paper, the role of pattern matching information theory is motivated and discussed...
The combination of mathematical models and uncertainty measures can be applied in the area of data m...
The demands for machine learning and knowledge extraction methods have been booming due to the unpre...
AbstractThis paper describes the outlier data mining and commonly used outlier mining methods, on th...
International audienceKöpf and Basin have discussed the relation between brute-force guessing attack...
Recent research has highlighted the practical benefits of subjective interestingness measures, which...
The discovery of patterns plays an important role in data mining. A pattern can be any type of regul...
In this thesis, we study objective interesting pattern mining processes on datasets such as used in ...
The idea of frequent pattern discovery is to find frequently occurring events in large databases. Su...
Many algorithms of machine learning use an entropy measure as optimization criterion. Among the wide...
Abstract. In exploratory data mining it is important to assess the significance of results. Given th...
International audienceEntropic measures such as conditional entropy or mutual information have been ...
Entropy is a central concept in physics and has deep connections with Information theory, which is o...
In the machine learning literature we can find numerous methods to solve classification problems. We...
Pattern Mining is one of the most researched topics in the data mining community. Literally hundreds...
Abstract — In this paper, the role of pattern matching information theory is motivated and discussed...
The combination of mathematical models and uncertainty measures can be applied in the area of data m...
The demands for machine learning and knowledge extraction methods have been booming due to the unpre...
AbstractThis paper describes the outlier data mining and commonly used outlier mining methods, on th...
International audienceKöpf and Basin have discussed the relation between brute-force guessing attack...
Recent research has highlighted the practical benefits of subjective interestingness measures, which...