The association rule mining has been very useful in many applications such as, market analysis, web data analysis, decision making, knowing customer trends etc. In transactional databases as time advances, new transactions are being added and obsolete transactions are discarded. Incremental mining deals with generating association rules based on available knowledge (obtained from mining of prev...

We present a reduction framework from ordinal regression to binary classification based on extended examples. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended examples with any binary classification algorithm, and constructing a ranking rule from the binary classifier. A weighted 0/1 loss of the binary c...

Knowledge based system need quality knowledge to provide an accurate decision. Due to irrelevant and incorrect information of expert during knowledge acquisition, the information extraction from data mining approach can reduce the biases and misconceptions of multiple experts. Moreover, the real world data which is huge and incomplete has made it complicated to extract only the quality knowledg...

This paper presents a comparison of two different techniques of Soft Computing (SC), in union with a novel approach of a hybrid model with Central Composite Design (CCD) with capacity of performing a rule reduction, without loss of reliability, and also performs a reduction of the computational time spent in prediction. Results obtained with this method show better performance thought generatin...