% This Fundamental Clustering Problems Suite (FCPS) may serve as a minimal test for new invented cluster algorithms. % % Every new invented algorithm should at least cluster the FCPS correctly. % % The data sets may be used as long as the following citation is referenced in any publication % concering any of this data: % % Alfred Ultsch, Clustering with SOM: U*C, in Proc. Workshop on Self Organizing Feature Maps ,pp 31-37 Paris 2005. % % main problem: none, i.e clear defined clusters % @relation Hepta @ATTRIBUTE x REAL @ATTRIBUTE y REAL @ATTRIBUTE z REAL @ATTRIBUTE class {1,2,3,4,5,6,7} @data -0.063274,0.027734,0.022683,1 -0.000731,0.048211,0.069198,1 -0.060767,-0.00908,0.053085,1 0.013252,-0.011876,0.055324,1 -0.054508,-0.003813,0.001738,1 0.02418,0.068275,0.033462,1 -0.029308,0.059849,-0.06326,1 -0.016453,0.013881,-0.013236,1 -0.042361,-0.059942,-0.026487,1 -0.01631,-0.036612,0.047928,1 0.03536,-0.04495,0.041474,1 -0.000287,-0.049496,-0.06343,1 -0.065931,-0.005381,-0.064899,1 0.009049,0.027976,0.01198,1 -0.005335,0.062592,-0.057507,1 -0.004175,0.064646,0.040856,1 0.091024,-0.031446,-0.014774,1 -0.077068,-0.035324,-0.03906,1 0.05515,-0.007045,0.078495,1 -0.033779,0.049066,0.026958,1 0.044954,-0.033716,0.011894,1 0.008785,0.016895,-0.09079,1 -0.061655,-0.023085,0.007996,1 -0.051274,0.054634,0.032257,1 0.04421,-0.062217,-0.018733,1 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