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In this paper, an algorithm is presented for extracting fuzzy rules from the Breast Cancer dataset. To extract fuzzy rules, an imitation based evolutionary algorithm is used called Krill Herd (KH). The KH algorithm is converted to a binary algorithm here, and is used for the classification problem with innovation, named Binary Krill Herd-based Fuzzy Rule Miner (BKH-FRM). Choosing the best krill and...
Data classification is an important branch of data mining and there are different methods for its implementation. Neural networks are one of the best ways for classification in machine learning. Structure and weights of neural network are most important in their precision. In recent years, due to the defects in gradient-based search algorithms in neural network training algorithms, metahuristic algorithms...
Data mining is a very popular technique which is successfully used in many areas. The aim of this paper is to present a Hybrid model for data classification from input datasets. The proposed model extracts knowledge using fuzzy rule based systems and performs classification task by fuzzy if-then rules. The proposed method performs the classification task and extracts required knowledge using fuzzy...
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