Add to ORKGInternational audienceWe consider the problem of feature selection, and we propose a new information-theoretic algorithm for ordering the features according to their relevance for classification. The novelty of our proposal consists in adopting Rényi min-entropy instead of the commonly used Shannon entropy. In particular, we adopt a notion of conditional min-entropy that has been recently proposed in the field of security and privacy, and that avoids the anomalies of previously-attempted definitions. This notion is strictly related to the Bayes error, which is a promising property for achieving accuracy in the classification. We evaluate our method on 2 classifiers and 3 datasets, and we show that it compares favorably with the correspondin...
International audienceWe propose a new family of latent variable models called max-margin min-entrop...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Variable selection methods play an important role in the field of attribute mining. The Naive Bayes ...
International audienceWe consider the problem of feature selection, and we propose a new information...
International audienceWe consider the problem of feature selection, and we propose a new information...
Institute for Communicating and Collaborative SystemsWe examine the task of feature selection, which...
Abstract. In this paper, we propose a novel filter for feature selection. Such filter relies on the ...
In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation...
We examine the task of feature selection, which is a method of forming simplified descriptions of co...
Along with the improvement of data acquisition techniques and the increasing computational capacity ...
Abstract—Feature selection problem has become the focus of much pattern classification research and ...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
International audienceWe propose a new family of latent variable models called max-margin min-entrop...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Variable selection methods play an important role in the field of attribute mining. The Naive Bayes ...
International audienceWe consider the problem of feature selection, and we propose a new information...
International audienceWe consider the problem of feature selection, and we propose a new information...
Institute for Communicating and Collaborative SystemsWe examine the task of feature selection, which...
Abstract. In this paper, we propose a novel filter for feature selection. Such filter relies on the ...
In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation...
We examine the task of feature selection, which is a method of forming simplified descriptions of co...
Along with the improvement of data acquisition techniques and the increasing computational capacity ...
Abstract—Feature selection problem has become the focus of much pattern classification research and ...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
International audienceWe propose a new family of latent variable models called max-margin min-entrop...
Data reduction is crucial in order to turn large datasets into information, the major purpose of dat...
Variable selection methods play an important role in the field of attribute mining. The Naive Bayes ...