The first three columns of each line in the following data correspond to input dimensions. The data may be used for clustering, using the first three columns alone. Some of the points fall in the vicinity of a corner of the unit cube, indicated by the fourth column that may be used as desired output for a classification problem. The same 3-dimensional input data may also be used for a 3-dimensional chessboard or ``grid'' problem, in which adjacent clusters belong to opposite classes; the fifth column in each line indicates the desired class-id. The same 3-dimensional input data can also be used to perform function approximation; the sixth and seventh columns in each line each give values for two functions of the three inputs. The sixth column represents x3(x1 + x2 + x3) - (x1*x1), and the seventh column represents tan(x1) + cos(x2) + sin(x3). 0.99 0.95 0.08 1 1 1.984 1.496 0.95 0.99 0.96 1 1 1.847 2.789 0.97 0.06 0.55 0 0 1.238 2.437 0.53 0.96 0.55 0 1 0.771 1.680 0.05 0.09 0.56 0 0 -0.282 1.680 0.02 0.10 0.01 1 1 0.002 1.025 0.01 0.97 0.55 0 0 -0.282 1.191 0.95 0.05 0.08 1 1 1.005 1.886 0.09 0.03 0.60 0 0 -0.291 1.769 0.92 0.03 0.52 0 0 1.074 2.365 0.07 0.54 0.56 0 1 -0.238 1.555 0.56 0.54 0.98 0 1 0.200 2.861 0.01 0.58 0.59 0 1 -0.336 1.507 0.56 0.50 0.02 0 1 0.604 1.429 0.92 0.50 0.54 0 1 1.524 2.279 0.56 0.09 0.54 0 1 0.373 2.124 0.93 0.91 0.51 0 0 1.942 1.969 0.59 0.10 0.92 0 0 0.090 2.869 0.95 0.59 0.56 0 1 1.699 2.274 0.99 0.94 0.01 1 1 1.917 1.430 0.94 0.59 0.60 0 1 1.654 2.324 0.51 0.55 0.06 0 1 0.571 1.404 0.60 0.09 0.09 0 0 0.457 1.648 0.94 0.55 0.53 0 1 1.603 2.250 0.98 0.57 0.04 0 0 1.541 1.710 0.92 0.09 0.08 1 1 1.007 1.874 0.02 0.99 0.59 0 0 -0.323 1.234 0.00 0.52 0.52 0 1 -0.266 1.442 0.96 0.50 0.99 0 0 1.392 3.218 0.01 0.59 0.59 0 1 -0.341 1.515 0.59 0.51 0.02 0 1 0.656 1.448 0.94 0.03 0.57 0 0 1.134 2.448 0.97 0.57 0.96 0 0 1.508 3.096 0.04 0.51 0.10 0 0 0.015 1.010 0.96 0.06 0.95 1 1 0.999 3.221 0.91 0.96 0.95 1 1 1.672 2.769 0.09 0.52 0.02 0 0 0.055 0.973 0.91 0.91 0.54 0 0 1.865 2.009 0.95 0.95 0.95 1 1 1.811 2.802 0.02 0.52 0.91 0 0 -0.798 2.187 0.58 0.53 0.94 0 1 0.291 2.793 0.56 0.51 0.52 0 0 0.617 1.980 0.98 0.04 0.58 0 0 1.229 2.491 0.99 0.58 0.98 0 0 1.562 3.146 0.95 0.96 0.56 0 0 2.033 2.013 0.90 0.01 0.10 1 1 0.902 1.885 0.94 0.98 0.53 0 0 2.038 1.947 0.92 0.51 0.94 0 0 1.287 3.049 0.91 0.51 0.03 0 0 1.311 1.688 0.98 0.05 0.05 1 1 1.055 1.878 0.10 0.98 0.54 0 0 -0.127 1.249 0.56 0.05 0.90 0 0 0.033 2.801 0.00 0.55 0.56 0 1 -0.314 1.492 0.97 0.90 0.07 1 1 1.880 1.515 0.59 0.02 0.95 0 0 0.020 2.972 0.52 0.09 1.00 0 0 -0.155 3.045 0.55 0.59 0.96 0 1 0.240 2.800 0.59 0.01 0.05 0 0 0.376 1.605 0.02 0.96 0.97 1 1 -0.893 2.050 0.52 0.52 0.92 0 1 0.167 2.692 0.56 0.08 0.10 0 0 0.404 1.625 0.01 0.56 0.53 0 1 -0.270 1.444 0.09 0.05 0.91 1 1 -0.740 2.386 0.57 0.59 0.59 0 0 0.659 2.038 0.09 0.02 0.54 0 0 -0.230 1.684 0.93 0.93 0.52 0 0 1.929 1.968 0.55 0.02 0.53 0 1 0.316 2.112 0.01 0.91 0.08 1 1 0.007 0.707 0.92 0.07 0.02 1 1 0.930 1.810 0.54 0.00 0.98 0 0 -0.128 2.999 0.06 0.07 0.57 0 0 -0.282 1.687 0.55 0.02 0.94 0 0 -0.047 2.897 0.91 0.59 0.00 0 0 1.366 1.622 0.90 0.03 0.94 1 1 0.812 3.143 0.05 0.54 0.98 0 0 -0.880 2.395 0.60 0.05 0.97 0 0 0.016 3.035 0.53 0.51 0.92 0 1 0.182 2.687 0.58 0.52 0.09 0 1 0.693 1.511 0.06 0.03 0.55 0 0 -0.268 1.669 0.57 0.51 0.54 0 0 0.625 2.013 0.03 0.58 0.56 0 1 -0.271 1.491 0.07 0.91 0.53 0 0 -0.178 1.277 0.92 0.60 0.57 0 1 1.605 2.265 0.51 0.91 0.06 0 0 0.754 1.161 0.10 0.99 0.09 1 1 0.108 0.737 0.59 0.05 0.95 0 0 0.029 2.959 0.91 0.60 0.01 0 0 1.395 1.632 0.96 0.54 0.92 0 0 1.491 2.991 0.50 0.04 0.96 0 0 -0.164 2.902 0.96 0.60 0.99 0 0 1.477 3.176 0.52 0.50 0.99 0 1 0.057 2.894 0.97 0.05 0.98 1 1 0.982 3.307 0.94 0.51 0.56 0 1 1.582 2.302 0.05 0.97 0.98 1 1 -0.860 2.118 0.52 0.54 0.57 0 0 0.528 2.001 0.53 0.95 0.06 0 0 0.810 1.149 0.07 0.08 0.06 1 1 0.010 1.121 0.07 0.51 0.98 0 0 -0.858 2.431 0.08 0.50 0.04 0 0 0.051 0.996 0.58 0.55 0.52 0 0 0.687 1.973 0.08 0.00 0.99 1 1 -0.888 2.592 0.93 0.60 0.03 0 0 1.445 1.659 0.50 0.90 0.59 0 1 0.650 1.779 0.06 0.98 0.09 1 1 0.060 0.711 0.91 0.90 0.99 1 1 1.553 2.942 0.09 0.52 0.98 0 0 -0.813 2.438 0.97 0.95 0.97 1 1 1.865 2.870