id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
hjic-126	Kenesei, T.; Abonyi, J.	Interpetable Support Vector Machines in Regression and Classification – Application in Process Engineering	2007	8	.pdf	application/pdf	5048	217	53	This paper describes a three-step technique how to use reduction techniques on trained SVM and SVR models to acquire transparent, but accurate fuzzy rule based classifier and fuzzy regression models. These techniques solve two cardinal problems: learning from experimental data by neural networks and support vector based techniques and embedding existing structured human knowledge into fuzzy models.	cache/hjic-126.pdf	txt/hjic-126.txt