  This paper proposed a model to predict the stock price based on combining
Self-Organizing Map (SOM) and fuzzy-Support Vector Machines (f-SVM). Extraction
of fuzzy rules from raw data based on the combining of statistical machine
learning models is base of this proposed approach. In the proposed model, SOM
is used as a clustering algorithm to partition the whole input space into the
several disjoint regions. For each partition, a set of fuzzy rules is extracted
based on a f-SVM combining model. Then fuzzy rules sets are used to predict the
test data using fuzzy inference algorithms. The performance of the proposed
approach is compared with other models using four data sets
