منابع مشابه
Improving Imbalanced data classification accuracy by using Fuzzy Similarity Measure and subtractive clustering
Classification is an one of the important parts of data mining and knowledge discovery. In most cases, the data that is utilized to used to training the clusters is not well distributed. This inappropriate distribution occurs when one class has a large number of samples but while the number of other class samples is naturally inherently low. In general, the methods of solving this kind of prob...
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Many semi-supervised clustering algorithms have been proposed to improve the clustering accuracy by effectively exploring the available side information that is usually in the form of pairwise constraints. However, there are two main shortcomings of the existing semi-supervised clustering algorithms. First, they have to deal with non-convex optimization problems, leading to clustering results t...
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We present a clustering method for continuous data. It defines local clusters into the (primary) data space but derives its similarity measure from the posterior distributions of additional discrete data that occur as pairs with the primary data. As a case study, enterprises are clustered by deriving the similarity measure from bankruptcy sensitivity. In another case study, a content-based clus...
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ژورنال
عنوان ژورنال: Journal of Computer Science and Technology
سال: 2008
ISSN: 1000-9000,1860-4749
DOI: 10.1007/s11390-008-9148-5