On the effectiveness of preprocessing methods when dealing with different levels of class imbalance
The present paper investigates the influence of both the imbalance ratio and the classifier on the performance of several resampling strategies to deal with imbalanced data sets. The study focuses on evaluating how learning is affected when different ...
Evolutionary-based selection of generalized instances for imbalanced classification
In supervised classification, we often encounter many real world problems in which the data do not have an equitable distribution among the different classes of the problem. In such cases, we are dealing with the so-called imbalanced data sets. One of ...
Class imbalance methods for translation initiation site recognition in DNA sequences
Translation initiation site (TIS) recognition is one of the first steps in gene structure prediction, and one of the common components in any gene recognition system. Many methods have been described in the literature to identify TIS in transcribed ...
Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking
This paper deals with the problem of supervised wrapper-based feature subset selection in datasets with a very large number of attributes. Recently the literature has contained numerous references to the use of hybrid selection algorithms: based on a ...
CMRules: Mining sequential rules common to several sequences
Sequential rule mining is an important data mining task used in a wide range of applications. However, current algorithms for discovering sequential rules common to several sequences use very restrictive definitions of sequential rules, which make them ...
Finding association rules in semantic web data
The amount of ontologies and semantic annotations available on the Web is constantly growing. This new type of complex and heterogeneous graph-structured data raises new challenges for the data mining community. In this paper, we present a novel method ...
Interpretable knowledge extraction from emergency call data based on fuzzy unsupervised decision tree
Nowadays, call centers are common in different areas of activity providing customer services, medical attention, security services, etc. Each type of call center has its own particularities but all call centers have to plan the availability of resources ...
Mining interestingness measures for string pattern mining
A novel method of detecting interesting patterns in strings is presented. A common way to refine the results of pattern mining algorithms is by using interestingness measures. However, the set of appropriate measures differs for each domain and problem. ...
