This research compares two algorithms that work with fuzzy data – the fuzzy PRISM algorithm and an algorithm for finding relevant attributes and membership functions – MDTF (merging – decision – table – first). Suitable data sets were searched for in the UCI Repository to examine the performance of both algorithms on real data. The most suitable data sets were Iris data set and Miles Per Gallon (MPG) data set. A series of experiments were carried out to compare the possibilities and working principles of each algorithm, depending on the size of the data set and the number of attributes used. As a result, recommendations for use of the algorithms are given, depending on the structure of the data set.