منابع مشابه
Missing Values and Learning of Fuzzy Rules
In this paper a technique is proposed to tolerate missing values based on a system of fuzzy rules for classi cation The presented method is mathematically solid but never theless easy and e cient to implement Three possible applications of this methodology are outlined the classi cation of patterns with an incomplete feature vector the com pletion of the input vector when a certain class is des...
متن کاملOn Missing Values and Fuzzy Rules
Numerous learning tasks involve incomplete or connicting attributes. Most algorithms that automatically nd a set of fuzzy rules are not well suited to tolerate missing values in the input vector, and the usual technique to substitute missing values by their mean or another constant value can be quite harmful. In this paper a technique is proposed to tolerate missing values during the classiicat...
متن کاملCompany MISSING VALUES AND LEARNING OF FUZZY
Received (received date) Revised (revised date) In this paper a technique is proposed to tolerate missing values based on a system of fuzzy rules for classiication. The presented method is mathematically solid but nevertheless easy and eecient to implement. Three possible applications of this methodology are outlined: the classiication of patterns with an incomplete feature vector, the completi...
متن کاملTreatment of Missing Values for Association Rules
Abs t r ac t . Agrawal et al. [2] have proposed a fast algorithm to explore very large transaction databases with association rules [1]. In many real world applications data are managed in relational databases where missing values are often inevitable. We will show, in this case, that association rules algorithms give bad results because they have been developed for transaction databases where ...
متن کاملFuzzy K-means clustering with missing values
Fuzzy K-means clustering algorithm is a popular approach for exploring the structure of a set of patterns, especially when the clusters are overlapping or fuzzy. However, the fuzzy K-means clustering algorithm cannot be applied when the real-life data contain missing values. In many cases, the number of patterns with missing values is so large that if these patterns are removed, then sufficient...
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ژورنال
عنوان ژورنال: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
سال: 1998
ISSN: 0218-4885,1793-6411
DOI: 10.1142/s021848859800015x