@article{(Open Science Index):https://publications.waset.org/pdf/15086, title = {Modeling Language for Constructing Solvers in Machine Learning: Reductionist Perspectives}, author = {Tsuyoshi Okita}, country = {}, institution = {}, abstract = {For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach in order to make a solver quickly. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem. It is noted that our formal modeling language is not intend for providing an efficient notation for data mining application, but for facilitating a designer who develops solvers in machine learning. }, journal = {International Journal of Computer and Information Engineering}, volume = {2}, number = {6}, year = {2008}, pages = {2256 - 2262}, ee = {https://publications.waset.org/pdf/15086}, url = {https://publications.waset.org/vol/18}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 18, 2008}, }