Now showing items 1-7 of 7
A Preprocessing Procedure for Haplotype Inference by Pure Parsimony
Haplotype data is especially important in the study of complex diseases since it contains more information than genotype data. However, obtaining haplotype data is technically difficult and expensive. Computational methods ...
Learning Probability Distributions over Permutations by Means of Fourier Coefficients
A large and increasing number of data mining domains consider data that can be represented as permutations. Therefore, it is important to devise new methods to learn predictive models over datasets of permutations. However, ...
An R package for permutations, Mallows and Generalized Mallows models
[EN]Probability models on permutations associate a probability value to each of the permutations on n items. This paper considers two popular probability models, the Mallows model and the Generalized Mallows model. We ...
Statistical model for the reproducibility in ranking based feature selection
Recently, concerns about the reproducibility of scientific studies have been growing among the scientific community, mainly due to the existing large quantity of irreproducible results. This has reach such an extent that ...
Sampling and learning the Mallows model under the Ulam distance
[EN]In this paper we deal with probability distributions over permutation spaces. The Probability model in use is the Mallows model. The distance for permutations that the model uses in the Ulam distance.
Sampling and learning the Mallows and Generalized Mallows models under the Cayley distance
[EN]The Mallows and Generalized Mallows models are compact yet powerful and natural ways of representing a probability distribution over the space of permutations. In this paper we deal with the problems of sampling and ...
Sampling and learning the Mallows and Weighted Mallows models under the Hamming distance
[EN]In this paper we deal with distributions over permutation spaces. The Mallows model is the mode l in use. The associated distance for permutations is the Hamming distance.