Encontrados 7 documentos, a visualizar página 1 de 1
Mining approximate motifs in time series
Azevedo, Paulo J.; Ferreira, Pedro Gabriel; Silva, Cândida G.; Brito, Rui M. M.The problem of discovering previously unknown frequent patterns in time series, also called motifs, has been recently introduced. A motif is a subseries pattern that appears a significant number of times. Results demonstrate that motifs may provide valuable insights about the data and have a wide range of applications in data mining tasks. The main motivation for this study was the need to mine time series data...
Visual interactive subgroup discovery with numerical properties of interest
Azevedo, Paulo J.; Jorge, Alípio M.; Pereira, FernandoSubgroup discovery consists in finding subsets of individuals from a given population which have distinctive collective properties with regard to one or more properties of interest. The interest of a subgroup can be objectively assessed using appropriate statistics, but it can also be evaluated by a data analyst or domain expert. In this paper we propose an approach to subgroup discovery via distribution rules ...
Query driven sequence pattern mining
Azevedo, Paulo J.; Ferreira, Pedro GabrielThe discovery of frequent patterns present in biological sequences has a large number of applications, ranging from classification, clustering and understanding sequence structure and function. This paper presents an algorithm that discovers frequent sequence patterns (motifs) present in a query sequence in respect to a database of sequences. The query is used to guide the mining process and thus only the patte...
An experiment with association rules and classification : post-bagging and conv...
Jorge, Alípio M.; Azevedo, Paulo J.In this paper we study a new technique we call post-bagging, which consists in resampling parts of a classification model rather then the data. We do this with a particular kind of model: large sets of classification association rules, and in combination with ordinary best rule and weighted voting approaches. We empirically evaluate the effects of the technique in terms of classification accuracy. We also discu...
Protein sequence pattern mining with constraints
Ferreira, Pedro Gabriel; Azevedo, Paulo J.Considering the characteristics of biological sequence databases, which typically have a small alphabet, a very long length and a relative small size (several hundreds of sequences), we propose a new sequence mining algorithm (gIL). gIL was developed for linear sequence pattern mining and results from the combination of some of the most efficient techniques used in sequence and itemset mining. The algorithm exh...
CAREN - A java based apriori implementation for classification purposes
Azevedo, Paulo J.In this document a java based implementation of the well know Apriori algorithm is described. The association rule generator is constructed toward the generation of classifiers. A detailed description of the data structures to store the itemsets is given along with the most important steps of the algorithm. Benchmarking and discussion on the main features is also presented.
Magic sets with full sharing
Azevedo, Paulo J.In this paper we study the relationship between tabulation and goal-oriented bottom-up evaluation of logic programs. Differences emerge when one tries to identify features of one evaluation method in the other. We show that to obtain the same effect as tabulation in top-down evaluation, one has to perform a careful {\em adornment} in programs to be evaluated bottom-up. Furthermore we propose an efficient algo...
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