Transformation rules for decomposing heterogeneous data into triples

Decomposing triples into cyclic designs

On Mining Fuzzy Classification Rules for Imbalanced Data

Fuzzy rule-based classification system (FRBCS) is a popular machine learning technique for classification purposes. One of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. However many cases the minority classes are more important than the majority ones. In this paper, we have extended ...

Finding association rules on heterogeneous genome data.

A novel approach for discovery of knowledge from genome data, which has been recently watched with interest in the research area of database, is applied to finding unified rules spreading over sequence, structure, and function of protein. As the result of experiments using data extracted from PDB, SWISS-PROT, and PROSITE, some association rules stating sequential/structural/functional aspects o...

Decomposing Matrices into Blocks

In this paper we investigate whether matrices arising from linear or integer programming problems can be decomposed into so-called bordered block diagonal form. More precisely, given some matrix A, we try to assign as many rows as possible to some number β of blocks of size κ such that no two rows assigned to different blocks intersect in a common column. Bordered block diagonal form is desirab...

On Mining Fuzzy Classification Rules for Imbalanced Data

Fuzzy rule-based classification system (FRBCS) is a popular machine learning technique for classification purposes. One of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. However many cases the minority classes are more important than the majority ones. In this paper, we have extended ...