In order to lower the classification cost and improve the performance of the classifier, this paper proposes the approach of the dynamic cost-sensitive ensemble classification based on extreme learning machine for imbalanced massive data streams (DCECIMDS). Firstly, this paper gives the method of concept drifts detection by extracting the attributive characters of imbalanced massive data stream...

Cost-effectiveness of a classification-based treatment system for sub-acute and chronic low back pain in primary care. Eur Spine J. Abstract Purpose: Identifying relevant subgroups in patients with low back pain (LBP) is considered important to guide physical therapy practice and to improve outcomes. The aim of the present study was to assess the cost-effectiveness of a modified version of Deli...

Domestic innovations and technology imports play important roles in boosting relative demand for skilled labor force. These factors are in turn influenced by domestic R&D investments and international trade. Using a translog cost function, this paper studies the effect of technology imports and other factors including output level and physical capital stock on the shares of skilled labor force ...

A new method for example-dependent cost (EDC) classification is proposed. The constitutes an extension of a recently introduced training algorithm neural networks. surrogate function estimate the Bayesian risk, where estimates conditional probabilities each class are defined in terms 1-D Parzen window estimator output (discriminative) This probability density modeled with objective allowing eas...

The article will consider options for classifying the costs of an enterprise, importance grouping types by individual characteristics, classification. purpose study is to determine most optimal cost classification as a goal. For this purpose, methods conducting research analysis in works well-known scientists and economists were used. author made proposals on innovation aimed at creating produc...

the main objective in classification of the nmr spectra of cancerous and healthy tissue , with high number of features is the prerequisites of the minimum number of samples. therefore the use of conventional classifier on this type of the data is not recommended. in the current work, different structures of the artificial neural networks (ann) were tried on classification of different cancerous...