most of data in multi-attribute decision making (madm) problems are changeable rather than constant and stable. therefore, sensitivity analysis after problem solving can effectively contribute to making accurate decisions. in this paper, we offer a new method for sensitivity analysis in multi-attribute decision making problems in which if the weights of one attribute changes, then we can deter...

In recent years, researchers have paid more and more attention on data mining of practical applications. Aimed to the problem of symptom classification of Chinese traditional medicine, this paper proposes a novel computing model based on the similarities among attributes of high dimension data to compute the similarity between any tuples. This model assumes data attributes as basic vectors of m...

We propose a clustering framework that supports clustering of datasets with mixed attribute type (numerical, categorical), while minimizing information loss during clustering. Real world datasets such as medical datasets and its ontology have mixed attribute type datasets. However, most conventional clustering algorithms have been designed and applied to datasets containing only single attribut...

Similarity measures play an important role in data mining, pattern recognition, decision making, machine learning, image process etc. Then, single valued neutrosophic sets (SVNSs) can describe and handle the indeterminate and inconsistent information, which fuzzy sets and intuitionistic fuzzy sets cannot describe and deal with. Therefore, the paper proposes new similarity meas-ures between SVNS...

Microarray gene dataset often contains high dimensionalities which cause difficulty in clustering and classification. Datasets containing huge number of genes lead to increased complexity and therefore, degradation of dataset handling performance. Often, all the measured features of these high-dimensional datasets are not relevant for understanding the underlying phenomena of interest. Dimensio...

The self-similarity of complex has extensive practical background in real world. It is similar to the phenomena of social relationships: “things of one kind come together, birds of a feather flock together”. Hence, we proposed the self-similarity network evolving model based on attributes similarity between the nodes. In network each node has the attribute value, by this computing similarity be...