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This paper presents a new approach to credit scoring by synthesizing simple nai??ve Bayesian classifier (SNBC) and the rough set theory. We adopted the combination of SNBC and rough set theory to build credit scoring model. The experiment was done on German Credit Database and showed that the model has a good prediction performance and has real world value upon application.
Automatic word-segmentation is vital for the reading, comprehension and translation of classics. However, large amount of special terms, allusions and proper names within the classics make it difficult for word segmentation. Taking classics of tea as the subject of research, a method was proposed using likelihood ratio statistics to decide two-character words candidate, three character words candidates...
In view of the fact that DBSCAN clustering algorithm can identify the data with arbitrary shape and one-pass clustering algorithm has the quick and efficient feature, this paper proposes a two-stage hybrid clustering algorithm. DBSCAN is improved to process the data with categorical attributes. By combining one-pass clustering algorithm with DBSCAN clustering algorithm, a two-stage hybrid clustering...
In this paper, a framework of region-of-interest (ROI) based multi-view video coding has been proposed to improve compression efficiency by properly segmenting the multi-view videos into different macroblock level ROI and encoding them separately. We define depth based ROI for multi-view video. Then, we propose a semantic low-complexity rode extraction algorithm based on multi-view video plus depth...
Web-based learning community allow educators to study how students learn (descriptive studies) and which learning strategies are most effective (causal/predictive studies). Since Web-based learning community are capable of collecting vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of students,...
Credit scoring models have been widely studied in academic world and the business community. Many novel approaches such as artificial neural networks (ANNs), rough sets, or decision trees have been proposed to increase the accuracy of credit scoring models. The C4.5 is a learning algorithm which adopts local search strategy, it cannot obtain the best decision rules. On the other hand, the simulated...
This paper studies hybrid dynamical evolutionary algorithm in the context of classification rule discovery. Nature inspired search algorithms such as genetic algorithms, Ant colonies and particle swarm optimization have been previously studied on data mining tasks, in particular, classification rule discovery. We extended this work by applying a hybrid algorithm which combines dynamical evolutionary...
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