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weight,height 0.132,0.757 0.722,0.888 0.095,0.804 0.633,0.53 0.472,0.701
0.294,0.183 0.179,0.874 0.023,0.664 0.116,0.978 0.054,0.786 0.394,0.97 0.165,0.372
0.654,0.906 0.486,0.871 0.237,0.691 0.584,0.99 0.133,0.396 0.068,0.234 0.114,0.464
0.108,0.241 0.392,0.697 0.049,0.361 0.169,0.877 0.709,0.863 0.046,0.646
0.069,0.525 0.432,0.841 0.366,0.888 0.386,0.57 0.576,0.912 0.312,0.559 0.177,0.398
0.084,0.316 0.462,0.701 0.166,0.459 0.573,0.714 0.173,0.379 0.198,0.955 0.807,0.96
0.081,0.758 0.501,0.901 0.45,0.844 0.126,0.326 0.569,0.785 0.229,0.984 0.14,0.643
0.065,0.777 0.7,0.868 0.219,0.628 0.19,0.401 0.428,0.794 0.118,0.39 0.575,0.724
0.423,0.956 0.638,0.911 0.079,0.57 0.057,0.94 0.334,0.576 0.045,0.252 0.384,0.846
0.097,0.537 0.147,0.826 0.604,0.859 0.097,0.649 0.056,0.615 0.15,0.506 0.139,0.764
0.025,0.332 0.626,0.782 0.27,0.946 0.577,0.902 0.033,0.473 0.773,0.938 0.303,0.68
0.576,0.721 0.326,0.989 0.407,0.719 0.406,0.921 0.649,0.905 0.579,0.841 0.095,0.621
0.254,0.646 0.093,0.57 0.126,0.42 0.387,0.71 0.063,0.996 0.016,0.867 0.161,0.885
0.01,0.7
0.154,0.564 0.565,0.961 0.34,0.482 0.443,0.763 0.741,0.948 0.339,0.761 0.87,0.132
0.704,0.564 0.842,0.052 0.903,0.01 0.621,0.691
1
weight,height 0.407,0.347 0.726,0.761 0.644,0.415 0.076,0.143 0.11,0.01 0.907,0.859
0.836,0.211 0.954,0.706 0.807,0.466 0.619,0.489 0.695,0.227 0.629,0.153 0.741,0.613
0.311,0.289 0.465,0.426 0.224,0.102 0.387,0.091 0.896,0.839 0.232,0.243 0.704,0.321
0.383,0.234 0.171,0.001 0.913,0.295 0.922,0.166 0.43,0.404 0.819,0.67 0.318,0.628
0.828,0.412 0.661,.556 0.509,0.572 0.07,0.167 0.71,0.347 0.862,0.08 0.856,0.622
0.916,0.075 0.408,0.398 0.78,0.341 0.677,0.14 0.8,0.07 0.598,0.446 0.309,0.358
0.429,0.414 0.446,0.328 0.769,0.487 0.854,0.903 0.857,0.428 0.599,0.222 0.904,0.941
0.853,0.151 0.92,0.609 0.817,0.183 0.482,0.33 0.412,0.326 0.261,0.097 0.572,0.177
0.627,0.6
0.836,0.967 0.518,0.44 0.831,0.59 0.842,0.102 0.205,0.325 0.549,0.317 0.93,0.89
0.897,0.993 0.53,0.091 0.39,0.477 0.917,0.368 0.537,0.431 0.001,0.033 0.664,0.141
0.129,0.123 0.876,0.342 0.481,0.567 0.909,0.804 0.721,0.837 0.662,0.772 0.796,0.566
0.9,0.032 0.702,0.386 0.887,0.003 0.634,0.377 0.686,0.329 0.532,0.63 0.495,0.394
0.633,0.706 0.217,0.33 0.999,0.726 0.945,0.274 0.935,0.321 0.213,0.012 0.165,0.014
0.781,0.607 0.902,0.957 0.868,0.201 0.198,0.006 0.052,0.385 0.433,0.986 0.357,0.554
0.303,0.889 0.061,0.814
1
Crim,Zn,Indus,Chas,Nox,Rm,Age,Dis,Rad,Tax,Ptratio,B,Lstat,Medv0.00632,18,2.31,0,0.538,6.575,65.2,4.09,1,296
1
Crim,Zn,Indus,Chas,Nox,Rm,Age,Dis,Rad,Tax,Ptratio,B,Lstat,Medv 0.00632,18,2.31,0,0.538,6.575,65.2,4.09,1,296
0.02731,0,7.07,0,0.469,6.421,78.9,4.9671,2,242,17.8,396.9,9.14,21.6 0.02729,0,7.07,0,0.469,7.185,61.1,4.9671,2,242,1
0.03237,0,2.18,0,0.458,6.998,45.8,6.0622,3,222,18.7,394.63,2.94,33.4 0.06905,0,2.18,0,0.458,7.147,54.2,6.0622,3,222,
0.02985,0,2.18,0,0.458,6.43,58.7,6.0622,3,222,18.7,394.12,5.21,28.7 0.08829,12.5,7.87,0,0.524,6.012,66.6,5.5605,5,31
0.14455,12.5,7.87,0,0.524,6.172,96.1,5.9505,5,311,15.2,396.9,19.15,27.1 0.21124,12.5,7.87,0,0.524,5.631,100,6.0821,5
0.17004,12.5,7.87,0,0.524,6.004,85.9,6.5921,5,311,15.2,386.71,17.1,18.9
0.22489,12.5,7.87,0,0.524,6.377,94.3,6.3467,5,311,15.2,392.52,20.45,15 0.11747,12.5,7.87,0,0.524,6.009,82.9,6.2267,5
0.09378,12.5,7.87,0,0.524,5.889,39,5.4509,5,311,15.2,390.5,15.71,21.7 0.62976,0,8.14,0,0.538,5.949,61.8,4.7075,4,307
0.63796,0,8.14,0,0.538,6.096,84.5,4.4619,4,307,21,380.02,10.26,18.2 0.62739,0,8.14,0,0.538,5.834,56.5,4.4986,4,307,2
1.05393,0,8.14,0,0.538,5.935,29.3,4.4986,4,307,21,386.85,6.58,23.1 0.7842,0,8.14,0,0.538,5.99,81.7,4.2579,4,307,21,3
0.80271,0,8.14,0,0.538,5.456,36.6,3.7965,4,307,21,288.99,11.69,20.2 0.7258,0,8.14,0,0.538,5.727,69.5,3.7965,4,307,21
1.25179,0,8.14,0,0.538,5.57,98.1,3.7979,4,307,21,376.57,21.02,13.6 0.85204,0,8.14,0,0.538,5.965,89.2,4.0123,4,307,21
1.23247,0,8.14,0,0.538,6.142,91.7,3.9769,4,307,21,396.9,18.72,15.2 0.98843,0,8.14,0,0.538,5.813,100,4.0952,4,307,21,
0.75026,0,8.14,0,0.538,5.924,94.1,4.3996,4,307,21,394.33,16.3,15.6 0.84054,0,8.14,0,0.538,5.599,85.7,4.4546,4,307,21
0.67191,0,8.14,0,0.538,5.813,90.3,4.682,4,307,21,376.88,14.81,16.6 0.95577,0,8.14,0,0.538,6.047,88.8,4.4534,4,307,21
0.77299,0,8.14,0,0.538,6.495,94.4,4.4547,4,307,21,387.94,12.8,18.4 1.00245,0,8.14,0,0.538,6.674,87.3,4.239,4,307,21,
1.13081,0,8.14,0,0.538,5.713,94.1,4.233,4,307,21,360.17,22.6,12.7 1.35472,0,8.14,0,0.538,6.072,100,4.175,4,307,21,37
1.38799,0,8.14,0,0.538,5.95,82,3.99,4,307,21,232.6,27.71,13.2 1.15172,0,8.14,0,0.538,5.701,95,3.7872,4,307,21,358.77
1.61282,0,8.14,0,0.538,6.096,96.9,3.7598,4,307,21,248.31,20.34,13.5 0.06417,0,5.96,0,0.499,5.933,68.2,3.3603,5,279,1
0.09744,0,5.96,0,0.499,5.841,61.4,3.3779,5,279,19.2,377.56,11.41,20 0.08014,0,5.96,0,0.499,5.85,41.5,3.9342,5,279,19
0.17505,0,5.96,0,0.499,5.966,30.2,3.8473,5,279,19.2,393.43,10.13,24.7 0.02763,75,2.95,0,0.428,6.595,21.8,5.4011,3,25
0.03359,75,2.95,0,0.428,7.024,15.8,5.4011,3,252,18.3,395.62,1.98,34.9 0.12744,0,6.91,0,0.448,6.77,2.9,5.7209,3,233,1
0.1415,0,6.91,0,0.448,6.169,6.6,5.7209,3,233,17.9,383.37,5.81,25.3 0.15936,0,6.91,0,0.448,6.211,6.5,5.7209,3,233,17.9
0.12269,0,6.91,0,0.448,6.069,40,5.7209,3,233,17.9,389.39,9.55,21.2 0.17142,0,6.91,0,0.448,5.682,33.8,5.1004,3,233,17
0.18836,0,6.91,0,0.448,5.786,33.3,5.1004,3,233,17.9,396.9,14.15,20 0.22927,0,6.91,0,0.448,6.03,85.5,5.6894,3,233,17.
0.25387,0,6.91,0,0.448,5.399,95.3,5.87,3,233,17.9,396.9,30.81,14.4 0.21977,0,6.91,0,0.448,5.602,62,6.0877,3,233,17.9
0.08873,21,5.64,0,0.439,5.963,45.7,6.8147,4,243,16.8,395.56,13.45,19.7 0.04337,21,5.64,0,0.439,6.115,63,6.8147,4,24
0.0536,21,5.64,0,0.439,6.511,21.1,6.8147,4,243,16.8,396.9,5.28,25 0.04981,21,5.64,0,0.439,5.998,21.4,6.8147,4,243,16
0.0136,75,4,0,0.41,5.888,47.6,7.3197,3,469,21.1,396.9,14.8,18.9 0.01311,90,1.22,0,0.403,7.249,21.9,8.6966,5,226,17.9
0.02055,85,0.74,0,0.41,6.383,35.7,9.1876,2,313,17.3,396.9,5.77,24.7 0.01432,100,1.32,0,0.411,6.816,40.5,8.3248,5,256
0.15445,25,5.13,0,0.453,6.145,29.2,7.8148,8,284,19.7,390.68,6.86,23.3 0.10328,25,5.13,0,0.453,5.927,47.2,6.932,8,284
0.14932,25,5.13,0,0.453,5.741,66.2,7.2254,8,284,19.7,395.11,13.15,18.7 0.17171,25,5.13,0,0.453,5.966,93.4,6.8185,8,2
0.11027,25,5.13,0,0.453,6.456,67.8,7.2255,8,284,19.7,396.9,6.73,22.2 0.1265,25,5.13,0,0.453,6.762,43.4,7.9809,8,284,
0.01951,17.5,1.38,0,0.4161,7.104,59.5,9.2229,3,216,18.6,393.24,8.05,33 0.03584,80,3.37,0,0.398,6.29,17.8,6.6115,4,33
0.04379,80,3.37,0,0.398,5.787,31.1,6.6115,4,337,16.1,396.9,10.24,19.4 0.05789,12.5,6.07,0,0.409,5.878,21.4,6.498,4,3
0.13554,12.5,6.07,0,0.409,5.594,36.8,6.498,4,345,18.9,396.9,13.09,17.4 0.12816,12.5,6.07,0,0.409,5.885,33,6.498,4,34
0.08826,0,10.81,0,0.413,6.417,6.6,5.2873,4,305,19.2,383.73,6.72,24.2 0.15876,0,10.81,0,0.413,5.961,17.5,5.2873,4,305
0.09164,0,10.81,0,0.413,6.065,7.8,5.2873,4,305,19.2,390.91,5.52,22.8 0.19539,0,10.81,0,0.413,6.245,6.2,5.2873,4,305,
0.07896,0,12.83,0,0.437,6.273,6,4.2515,5,398,18.7,394.92,6.78,24.1 0.09512,0,12.83,0,0.437,6.286,45,4.5026,5,398,18
0.10153,0,12.83,0,0.437,6.279,74.5,4.0522,5,398,18.7,373.66,11.97,20 0.08707,0,12.83,0,0.437,6.14,45.8,4.0905,5,398
0.05646,0,12.83,0,0.437,6.232,53.7,5.0141,5,398,18.7,386.4,12.34,21.2 0.08387,0,12.83,0,0.437,5.874,36.6,4.5026,5,39
0.04113,25,4.86,0,0.426,6.727,33.5,5.4007,4,281,19,396.9,5.29,28 0.04462,25,4.86,0,0.426,6.619,70.4,5.4007,4,281,19
0.03659,25,4.86,0,0.426,6.302,32.2,5.4007,4,281,19,396.9,6.72,24.8 0.03551,25,4.86,0,0.426,6.167,46.7,5.4007,4,281,1
0.05059,0,4.49,0,0.449,6.389,48,4.7794,3,247,18.5,396.9,9.62,23.9 0.05735,0,4.49,0,0.449,6.63,56.1,4.4377,3,247,18.5
0.05188,0,4.49,0,0.449,6.015,45.1,4.4272,3,247,18.5,395.99,12.86,22.5 0.07151,0,4.49,0,0.449,6.121,56.8,3.7476,3,247
0.0566,0,3.41,0,0.489,7.007,86.3,3.4217,2,270,17.8,396.9,5.5,23.6 0.05302,0,3.41,0,0.489,7.079,63.1,3.4145,2,270,17.8
1
0.04684,0,3.41,0,0.489,6.417,66.1,3.0923,2,270,17.8,392.18,8.81,22.6 0.03932,0,3.41,0,0.489,6.405,73.9,3.0921,2,270,
0.04203,28,15.04,0,0.464,6.442,53.6,3.6659,4,270,18.2,395.01,8.16,22.9 0.02875,28,15.04,0,0.464,6.211,28.9,3.6659,4
0.04294,28,15.04,0,0.464,6.249,77.3,3.615,4,270,18.2,396.9,10.59,20.6 0.12204,0,2.89,0,0.445,6.625,57.8,3.4952,2,276
0.11504,0,2.89,0,0.445,6.163,69.6,3.4952,2,276,18,391.83,11.34,21.4 0.12083,0,2.89,0,0.445,8.069,76,3.4952,2,276,18
0.08187,0,2.89,0,0.445,7.82,36.9,3.4952,2,276,18,393.53,3.57,43.8 0.0686,0,2.89,0,0.445,7.416,62.5,3.4952,2,276,18,3
0.14866,0,8.56,0,0.52,6.727,79.9,2.7778,5,384,20.9,394.76,9.42,27.5 0.11432,0,8.56,0,0.52,6.781,71.3,2.8561,5,384,20
0.22876,0,8.56,0,0.52,6.405,85.4,2.7147,5,384,20.9,70.8,10.63,18.6 0.21161,0,8.56,0,0.52,6.137,87.4,2.7147,5,384,20.9
0.1396,0,8.56,0,0.52,6.167,90,2.421,5,384,20.9,392.69,12.33,20.1 0.13262,0,8.56,0,0.52,5.851,96.7,2.1069,5,384,20.9,3
0.1712,0,8.56,0,0.52,5.836,91.9,2.211,5,384,20.9,395.67,18.66,19.5 0.13117,0,8.56,0,0.52,6.127,85.2,2.1224,5,384,20.9
0.12802,0,8.56,0,0.52,6.474,97.1,2.4329,5,384,20.9,395.24,12.27,19.8 0.26363,0,8.56,0,0.52,6.229,91.2,2.5451,5,384,2
0.10793,0,8.56,0,0.52,6.195,54.4,2.7778,5,384,20.9,393.49,13,21.7 0.10084,0,10.01,0,0.547,6.715,81.6,2.6775,6,432,17
0.12329,0,10.01,0,0.547,5.913,92.9,2.3534,6,432,17.8,394.95,16.21,18.8 0.22212,0,10.01,0,0.547,6.092,95.4,2.548,6,43
0.14231,0,10.01,0,0.547,6.254,84.2,2.2565,6,432,17.8,388.74,10.45,18.5 0.17134,0,10.01,0,0.547,5.928,88.2,2.4631,6,4
0.13158,0,10.01,0,0.547,6.176,72.5,2.7301,6,432,17.8,393.3,12.04,21.2 0.15098,0,10.01,0,0.547,6.021,82.6,2.7474,6,43
0.13058,0,10.01,0,0.547,5.872,73.1,2.4775,6,432,17.8,338.63,15.37,20.4 0.14476,0,10.01,0,0.547,5.731,65.2,2.7592,6,4
0.06899,0,25.65,0,0.581,5.87,69.7,2.2577,2,188,19.1,389.15,14.37,22 0.07165,0,25.65,0,0.581,6.004,84.1,2.1974,2,188
0.09299,0,25.65,0,0.581,5.961,92.9,2.0869,2,188,19.1,378.09,17.93,20.5 0.15038,0,25.65,0,0.581,5.856,97,1.9444,2,18
0.09849,0,25.65,0,0.581,5.879,95.8,2.0063,2,188,19.1,379.38,17.58,18.8 0.16902,0,25.65,0,0.581,5.986,88.4,1.9929,2,1
0.38735,0,25.65,0,0.581,5.613,95.6,1.7572,2,188,19.1,359.29,27.26,15.7 0.25915,0,21.89,0,0.624,5.693,96,1.7883,4,43
0.32543,0,21.89,0,0.624,6.431,98.8,1.8125,4,437,21.2,396.9,15.39,18 0.88125,0,21.89,0,0.624,5.637,94.7,1.9799,4,437
0.34006,0,21.89,0,0.624,6.458,98.9,2.1185,4,437,21.2,395.04,12.6,19.2 1.19294,0,21.89,0,0.624,6.326,97.7,2.271,4,437
0.59005,0,21.89,0,0.624,6.372,97.9,2.3274,4,437,21.2,385.76,11.12,23 0.32982,0,21.89,0,0.624,5.822,95.4,2.4699,4,43
0.97617,0,21.89,0,0.624,5.757,98.4,2.346,4,437,21.2,262.76,17.31,15.6 0.55778,0,21.89,0,0.624,6.335,98.2,2.1107,4,43
0.32264,0,21.89,0,0.624,5.942,93.5,1.9669,4,437,21.2,378.25,16.9,17.4 0.35233,0,21.89,0,0.624,6.454,98.4,1.8498,4,43
0.2498,0,21.89,0,0.624,5.857,98.2,1.6686,4,437,21.2,392.04,21.32,13.3 0.54452,0,21.89,0,0.624,6.151,97.9,1.6687,4,43
0.2909,0,21.89,0,0.624,6.174,93.6,1.6119,4,437,21.2,388.08,24.16,14 1.62864,0,21.89,0,0.624,5.019,100,1.4394,4,437,
3.32105,0,19.58,1,0.871,5.403,100,1.3216,5,403,14.7,396.9,26.82,13.4 4.0974,0,19.58,0,0.871,5.468,100,1.4118,5,403,1
2.77974,0,19.58,0,0.871,4.903,97.8,1.3459,5,403,14.7,396.9,29.29,11.8 2.37934,0,19.58,0,0.871,6.13,100,1.4191,5,403,
2.15505,0,19.58,0,0.871,5.628,100,1.5166,5,403,14.7,169.27,16.65,15.6 2.36862,0,19.58,0,0.871,4.926,95.7,1.4608,5,40
2.33099,0,19.58,0,0.871,5.186,93.8,1.5296,5,403,14.7,356.99,28.32,17.8 2.73397,0,19.58,0,0.871,5.597,94.9,1.5257,5,4
1.6566,0,19.58,0,0.871,6.122,97.3,1.618,5,403,14.7,372.8,14.1,21.5 1.49632,0,19.58,0,0.871,5.404,100,1.5916,5,403,14
1.12658,0,19.58,1,0.871,5.012,88,1.6102,5,403,14.7,343.28,12.12,15.3 2.14918,0,19.58,0,0.871,5.709,98.5,1.6232,5,403
1.41385,0,19.58,1,0.871,6.129,96,1.7494,5,403,14.7,321.02,15.12,17 3.53501,0,19.58,1,0.871,6.152,82.6,1.7455,5,403,1
2.44668,0,19.58,0,0.871,5.272,94,1.7364,5,403,14.7,88.63,16.14,13.1 1.22358,0,19.58,0,0.605,6.943,97.4,1.8773,5,403,
1.34284,0,19.58,0,0.605,6.066,100,1.7573,5,403,14.7,353.89,6.43,24.3 1.42502,0,19.58,0,0.871,6.51,100,1.7659,5,403,1
1.27346,0,19.58,1,0.605,6.25,92.6,1.7984,5,403,14.7,338.92,5.5,27 1.46336,0,19.58,0,0.605,7.489,90.8,1.9709,5,403,14
1.83377,0,19.58,1,0.605,7.802,98.2,2.0407,5,403,14.7,389.61,1.92,50 1.51902,0,19.58,1,0.605,8.375,93.9,2.162,5,403,1
2.24236,0,19.58,0,0.605,5.854,91.8,2.422,5,403,14.7,395.11,11.64,22.7 2.924,0,19.58,0,0.605,6.101,93,2.2834,5,403,14
2.01019,0,19.58,0,0.605,7.929,96.2,2.0459,5,403,14.7,369.3,3.7,50 1.80028,0,19.58,0,0.605,5.877,79.2,2.4259,5,403,14
2.3004,0,19.58,0,0.605,6.319,96.1,2.1,5,403,14.7,297.09,11.1,23.8 2.44953,0,19.58,0,0.605,6.402,95.2,2.2625,5,403,14
1.20742,0,19.58,0,0.605,5.875,94.6,2.4259,5,403,14.7,292.29,14.43,17.4 2.3139,0,19.58,0,0.605,5.88,97.3,2.3887,5,403
0.13914,0,4.05,0,0.51,5.572,88.5,2.5961,5,296,16.6,396.9,14.69,23.1 0.09178,0,4.05,0,0.51,6.416,84.1,2.6463,5,296,16
0.08447,0,4.05,0,0.51,5.859,68.7,2.7019,5,296,16.6,393.23,9.64,22.6 0.06664,0,4.05,0,0.51,6.546,33.1,3.1323,5,296,16
0.07022,0,4.05,0,0.51,6.02,47.2,3.5549,5,296,16.6,393.23,10.11,23.2 0.05425,0,4.05,0,0.51,6.315,73.4,3.3175,5,296,16
0.06642,0,4.05,0,0.51,6.86,74.4,2.9153,5,296,16.6,391.27,6.92,29.9 0.0578,0,2.46,0,0.488,6.98,58.4,2.829,3,193,17.8,3
0.06588,0,2.46,0,0.488,7.765,83.3,2.741,3,193,17.8,395.56,7.56,39.8 0.06888,0,2.46,0,0.488,6.144,62.2,2.5979,3,193,1
2
0.09103,0,2.46,0,0.488,7.155,92.2,2.7006,3,193,17.8,394.12,4.82,37.9 0.10008,0,2.46,0,0.488,6.563,95.6,2.847,3,193,1
0.08308,0,2.46,0,0.488,5.604,89.8,2.9879,3,193,17.8,391,13.98,26.4 0.06047,0,2.46,0,0.488,6.153,68.8,3.2797,3,193,17
0.05602,0,2.46,0,0.488,7.831,53.6,3.1992,3,193,17.8,392.63,4.45,50 0.07875,45,3.44,0,0.437,6.782,41.1,3.7886,5,398,1
0.12579,45,3.44,0,0.437,6.556,29.1,4.5667,5,398,15.2,382.84,4.56,29.8 0.0837,45,3.44,0,0.437,7.185,38.9,4.5667,5,398
0.09068,45,3.44,0,0.437,6.951,21.5,6.4798,5,398,15.2,377.68,5.1,37 0.06911,45,3.44,0,0.437,6.739,30.8,6.4798,5,398,1
0.08664,45,3.44,0,0.437,7.178,26.3,6.4798,5,398,15.2,390.49,2.87,36.4 0.02187,60,2.93,0,0.401,6.8,9.9,6.2196,1,265,1
0.01439,60,2.93,0,0.401,6.604,18.8,6.2196,1,265,15.6,376.7,4.38,29.1 0.01381,80,0.46,0,0.422,7.875,32,5.6484,4,255,1
0.04011,80,1.52,0,0.404,7.287,34.1,7.309,2,329,12.6,396.9,4.08,33.3 0.04666,80,1.52,0,0.404,7.107,36.6,7.309,2,329,1
0.03768,80,1.52,0,0.404,7.274,38.3,7.309,2,329,12.6,392.2,6.62,34.6 0.0315,95,1.47,0,0.403,6.975,15.3,7.6534,3,402,1
0.01778,95,1.47,0,0.403,7.135,13.9,7.6534,3,402,17,384.3,4.45,32.9 0.03445,82.5,2.03,0,0.415,6.162,38.4,6.27,2,348,1
0.02177,82.5,2.03,0,0.415,7.61,15.7,6.27,2,348,14.7,395.38,3.11,42.3 0.0351,95,2.68,0,0.4161,7.853,33.2,5.118,4,224,1
0.02009,95,2.68,0,0.4161,8.034,31.9,5.118,4,224,14.7,390.55,2.88,50 0.13642,0,10.59,0,0.489,5.891,22.3,3.9454,4,277
0.22969,0,10.59,0,0.489,6.326,52.5,4.3549,4,277,18.6,394.87,10.97,24.4 0.25199,0,10.59,0,0.489,5.783,72.7,4.3549,4,2
0.13587,0,10.59,1,0.489,6.064,59.1,4.2392,4,277,18.6,381.32,14.66,24.4 0.43571,0,10.59,1,0.489,5.344,100,3.875,4,27
0.17446,0,10.59,1,0.489,5.96,92.1,3.8771,4,277,18.6,393.25,17.27,21.7 0.37578,0,10.59,1,0.489,5.404,88.6,3.665,4,277
0.21719,0,10.59,1,0.489,5.807,53.8,3.6526,4,277,18.6,390.94,16.03,22.4 0.14052,0,10.59,0,0.489,6.375,32.3,3.9454,4,2
0.28955,0,10.59,0,0.489,5.412,9.8,3.5875,4,277,18.6,348.93,29.55,23.7 0.19802,0,10.59,0,0.489,6.182,42.4,3.9454,4,27
0.0456,0,13.89,1,0.55,5.888,56,3.1121,5,276,16.4,392.8,13.51,23.3 0.07013,0,13.89,0,0.55,6.642,85.1,3.4211,5,276,16.
0.11069,0,13.89,1,0.55,5.951,93.8,2.8893,5,276,16.4,396.9,17.92,21.5 0.11425,0,13.89,1,0.55,6.373,92.4,3.3633,5,276,
0.35809,0,6.2,1,0.507,6.951,88.5,2.8617,8,307,17.4,391.7,9.71,26.7 0.40771,0,6.2,1,0.507,6.164,91.3,3.048,8,307,17.4,
0.62356,0,6.2,1,0.507,6.879,77.7,3.2721,8,307,17.4,390.39,9.93,27.5 0.6147,0,6.2,0,0.507,6.618,80.8,3.2721,8,307,17.4
0.31533,0,6.2,0,0.504,8.266,78.3,2.8944,8,307,17.4,385.05,4.14,44.8 0.52693,0,6.2,0,0.504,8.725,83,2.8944,8,307,17.4
0.38214,0,6.2,0,0.504,8.04,86.5,3.2157,8,307,17.4,387.38,3.13,37.6 0.41238,0,6.2,0,0.504,7.163,79.9,3.2157,8,307,17.4
0.29819,0,6.2,0,0.504,7.686,17,3.3751,8,307,17.4,377.51,3.92,46.7 0.44178,0,6.2,0,0.504,6.552,21.4,3.3751,8,307,17.4
0.537,0,6.2,0,0.504,5.981,68.1,3.6715,8,307,17.4,378.35,11.65,24.3 0.46296,0,6.2,0,0.504,7.412,76.9,3.6715,8,307,17.4
0.57529,0,6.2,0,0.507,8.337,73.3,3.8384,8,307,17.4,385.91,2.47,41.7 0.33147,0,6.2,0,0.507,8.247,70.4,3.6519,8,307,17
0.44791,0,6.2,1,0.507,6.726,66.5,3.6519,8,307,17.4,360.2,8.05,29 0.33045,0,6.2,0,0.507,6.086,61.5,3.6519,8,307,17.4,3
0.52058,0,6.2,1,0.507,6.631,76.5,4.148,8,307,17.4,388.45,9.54,25.1 0.51183,0,6.2,0,0.507,7.358,71.6,4.148,8,307,17.4,
0.08244,30,4.93,0,0.428,6.481,18.5,6.1899,6,300,16.6,379.41,6.36,23.7 0.09252,30,4.93,0,0.428,6.606,42.2,6.1899,6,30
0.11329,30,4.93,0,0.428,6.897,54.3,6.3361,6,300,16.6,391.25,11.38,22 0.10612,30,4.93,0,0.428,6.095,65.1,6.3361,6,30
0.1029,30,4.93,0,0.428,6.358,52.9,7.0355,6,300,16.6,372.75,11.22,22.2 0.12757,30,4.93,0,0.428,6.393,7.8,7.0355,6,300
0.20608,22,5.86,0,0.431,5.593,76.5,7.9549,7,330,19.1,372.49,12.5,17.6 0.19133,22,5.86,0,0.431,5.605,70.2,7.9549,7,33
0.33983,22,5.86,0,0.431,6.108,34.9,8.0555,7,330,19.1,390.18,9.16,24.3 0.19657,22,5.86,0,0.431,6.226,79.2,8.0555,7,33
0.16439,22,5.86,0,0.431,6.433,49.1,7.8265,7,330,19.1,374.71,9.52,24.5 0.19073,22,5.86,0,0.431,6.718,17.5,7.8265,7,33
0.1403,22,5.86,0,0.431,6.487,13,7.3967,7,330,19.1,396.28,5.9,24.4 0.21409,22,5.86,0,0.431,6.438,8.9,7.3967,7,330,19.
0.08221,22,5.86,0,0.431,6.957,6.8,8.9067,7,330,19.1,386.09,3.53,29.6 0.36894,22,5.86,0,0.431,8.259,8.4,8.9067,7,330,
0.04819,80,3.64,0,0.392,6.108,32,9.2203,1,315,16.4,392.89,6.57,21.9 0.03548,80,3.64,0,0.392,5.876,19.1,9.2203,1,315
0.01538,90,3.75,0,0.394,7.454,34.2,6.3361,3,244,15.9,386.34,3.11,44 0.61154,20,3.97,0,0.647,8.704,86.9,1.801,5,264,1
0.66351,20,3.97,0,0.647,7.333,100,1.8946,5,264,13,383.29,7.79,36 0.65665,20,3.97,0,0.647,6.842,100,2.0107,5,264,13,
0.54011,20,3.97,0,0.647,7.203,81.8,2.1121,5,264,13,392.8,9.59,33.8 0.53412,20,3.97,0,0.647,7.52,89.4,2.1398,5,264,13
0.52014,20,3.97,0,0.647,8.398,91.5,2.2885,5,264,13,386.86,5.91,48.8 0.82526,20,3.97,0,0.647,7.327,94.5,2.0788,5,264
0.55007,20,3.97,0,0.647,7.206,91.6,1.9301,5,264,13,387.89,8.1,36.5 0.76162,20,3.97,0,0.647,5.56,62.8,1.9865,5,264,13
0.7857,20,3.97,0,0.647,7.014,84.6,2.1329,5,264,13,384.07,14.79,30.7 0.57834,20,3.97,0,0.575,8.297,67,2.4216,5,264,1
0.5405,20,3.97,0,0.575,7.47,52.6,2.872,5,264,13,390.3,3.16,43.5 0.09065,20,6.96,1,0.464,5.92,61.5,3.9175,3,223,18.6,3
0.29916,20,6.96,0,0.464,5.856,42.1,4.429,3,223,18.6,388.65,13,21.1 0.16211,20,6.96,0,0.464,6.24,16.3,4.429,3,223,18.
0.1146,20,6.96,0,0.464,6.538,58.7,3.9175,3,223,18.6,394.96,7.73,24.4 0.22188,20,6.96,1,0.464,7.691,51.8,4.3665,3,223
3
0.05644,40,6.41,1,0.447,6.758,32.9,4.0776,4,254,17.6,396.9,3.53,32.4 0.09604,40,6.41,0,0.447,6.854,42.8,4.2673,4,254
0.10469,40,6.41,1,0.447,7.267,49,4.7872,4,254,17.6,389.25,6.05,33.2 0.06127,40,6.41,1,0.447,6.826,27.6,4.8628,4,254
0.07978,40,6.41,0,0.447,6.482,32.1,4.1403,4,254,17.6,396.9,7.19,29.1 0.21038,20,3.33,0,0.4429,6.812,32.2,4.1007,5,21
0.03578,20,3.33,0,0.4429,7.82,64.5,4.6947,5,216,14.9,387.31,3.76,45.4 0.03705,20,3.33,0,0.4429,6.968,37.2,5.2447,5,2
0.06129,20,3.33,1,0.4429,7.645,49.7,5.2119,5,216,14.9,377.07,3.01,46 0.01501,90,1.21,1,0.401,7.923,24.8,5.885,1,198
0.00906,90,2.97,0,0.4,7.088,20.8,7.3073,1,285,15.3,394.72,7.85,32.2 0.01096,55,2.25,0,0.389,6.453,31.9,7.3073,1,300,
0.01965,80,1.76,0,0.385,6.23,31.5,9.0892,1,241,18.2,341.6,12.93,20.1 0.03871,52.5,5.32,0,0.405,6.209,31.3,7.3172,6,2
0.0459,52.5,5.32,0,0.405,6.315,45.6,7.3172,6,293,16.6,396.9,7.6,22.3 0.04297,52.5,5.32,0,0.405,6.565,22.9,7.3172,6,29
0.03502,80,4.95,0,0.411,6.861,27.9,5.1167,4,245,19.2,396.9,3.33,28.5 0.07886,80,4.95,0,0.411,7.148,27.7,5.1167,4,245
0.03615,80,4.95,0,0.411,6.63,23.4,5.1167,4,245,19.2,396.9,4.7,27.9 0.08265,0,13.92,0,0.437,6.127,18.4,5.5027,4,289,1
0.08199,0,13.92,0,0.437,6.009,42.3,5.5027,4,289,16,396.9,10.4,21.7 0.12932,0,13.92,0,0.437,6.678,31.1,5.9604,4,289,1
0.05372,0,13.92,0,0.437,6.549,51,5.9604,4,289,16,392.85,7.39,27.1 0.14103,0,13.92,0,0.437,5.79,58,6.32,4,289,16,396
0.06466,70,2.24,0,0.4,6.345,20.1,7.8278,5,358,14.8,368.24,4.97,22.5 0.05561,70,2.24,0,0.4,7.041,10,7.8278,5,358,14.8
0.04417,70,2.24,0,0.4,6.871,47.4,7.8278,5,358,14.8,390.86,6.07,24.8 0.03537,34,6.09,0,0.433,6.59,40.4,5.4917,7,329,1
0.09266,34,6.09,0,0.433,6.495,18.4,5.4917,7,329,16.1,383.61,8.67,26.4 0.1,34,6.09,0,0.433,6.982,17.7,5.4917,7,329,16
0.05515,33,2.18,0,0.472,7.236,41.1,4.022,7,222,18.4,393.68,6.93,36.1 0.05479,33,2.18,0,0.472,6.616,58.1,3.37,7,222,1
0.07503,33,2.18,0,0.472,7.42,71.9,3.0992,7,222,18.4,396.9,6.47,33.4 0.04932,33,2.18,0,0.472,6.849,70.3,3.1827,7,222,
0.49298,0,9.9,0,0.544,6.635,82.5,3.3175,4,304,18.4,396.9,4.54,22.8 0.3494,0,9.9,0,0.544,5.972,76.7,3.1025,4,304,18.4,
2.63548,0,9.9,0,0.544,4.973,37.8,2.5194,4,304,18.4,350.45,12.64,16.1 0.79041,0,9.9,0,0.544,6.122,52.8,2.6403,4,304,1
0.26169,0,9.9,0,0.544,6.023,90.4,2.834,4,304,18.4,396.3,11.72,19.4 0.26938,0,9.9,0,0.544,6.266,82.8,3.2628,4,304,18.4
0.3692,0,9.9,0,0.544,6.567,87.3,3.6023,4,304,18.4,395.69,9.28,23.8 0.25356,0,9.9,0,0.544,5.705,77.7,3.945,4,304,18.4,
0.31827,0,9.9,0,0.544,5.914,83.2,3.9986,4,304,18.4,390.7,18.33,17.8 0.24522,0,9.9,0,0.544,5.782,71.7,4.0317,4,304,18
0.40202,0,9.9,0,0.544,6.382,67.2,3.5325,4,304,18.4,395.21,10.36,23.1 0.47547,0,9.9,0,0.544,6.113,58.8,4.0019,4,304,1
0.1676,0,7.38,0,0.493,6.426,52.3,4.5404,5,287,19.6,396.9,7.2,23.8 0.18159,0,7.38,0,0.493,6.376,54.3,4.5404,5,287,19.6
0.35114,0,7.38,0,0.493,6.041,49.9,4.7211,5,287,19.6,396.9,7.7,20.4 0.28392,0,7.38,0,0.493,5.708,74.3,4.7211,5,287,19
0.34109,0,7.38,0,0.493,6.415,40.1,4.7211,5,287,19.6,396.9,6.12,25 0.19186,0,7.38,0,0.493,6.431,14.7,5.4159,5,287,19.
0.30347,0,7.38,0,0.493,6.312,28.9,5.4159,5,287,19.6,396.9,6.15,23 0.24103,0,7.38,0,0.493,6.083,43.7,5.4159,5,287,19.
0.06617,0,3.24,0,0.46,5.868,25.8,5.2146,4,430,16.9,382.44,9.97,19.3 0.06724,0,3.24,0,0.46,6.333,17.2,5.2146,4,430,16
0.04544,0,3.24,0,0.46,6.144,32.2,5.8736,4,430,16.9,368.57,9.09,19.8 0.05023,35,6.06,0,0.4379,5.706,28.4,6.6407,1,304
0.03466,35,6.06,0,0.4379,6.031,23.3,6.6407,1,304,16.9,362.25,7.83,19.4 0.05083,0,5.19,0,0.515,6.316,38.1,6.4584,5,22
0.03738,0,5.19,0,0.515,6.31,38.5,6.4584,5,224,20.2,389.4,6.75,20.7 0.03961,0,5.19,0,0.515,6.037,34.5,5.9853,5,224,20
0.03427,0,5.19,0,0.515,5.869,46.3,5.2311,5,224,20.2,396.9,9.8,19.5 0.03041,0,5.19,0,0.515,5.895,59.6,5.615,5,224,20.2
0.03306,0,5.19,0,0.515,6.059,37.3,4.8122,5,224,20.2,396.14,8.51,20.6 0.05497,0,5.19,0,0.515,5.985,45.4,4.8122,5,224,
0.06151,0,5.19,0,0.515,5.968,58.5,4.8122,5,224,20.2,396.9,9.29,18.7 0.01301,35,1.52,0,0.442,7.241,49.3,7.0379,1,284,
0.02498,0,1.89,0,0.518,6.54,59.7,6.2669,1,422,15.9,389.96,8.65,16.5 0.02543,55,3.78,0,0.484,6.696,56.4,5.7321,5,370,
0.03049,55,3.78,0,0.484,6.874,28.1,6.4654,5,370,17.6,387.97,4.61,31.2 0.03113,0,4.39,0,0.442,6.014,48.5,8.0136,3,352
0.06162,0,4.39,0,0.442,5.898,52.3,8.0136,3,352,18.8,364.61,12.67,17.2 0.0187,85,4.15,0,0.429,6.516,27.7,8.5353,4,351
0.01501,80,2.01,0,0.435,6.635,29.7,8.344,4,280,17,390.94,5.99,24.5 0.02899,40,1.25,0,0.429,6.939,34.5,8.7921,1,335,1
0.06211,40,1.25,0,0.429,6.49,44.4,8.7921,1,335,19.7,396.9,5.98,22.9 0.0795,60,1.69,0,0.411,6.579,35.9,10.7103,4,411,
0.07244,60,1.69,0,0.411,5.884,18.5,10.7103,4,411,18.3,392.33,7.79,18.6 0.01709,90,2.02,0,0.41,6.728,36.1,12.1265,5,1
0.04301,80,1.91,0,0.413,5.663,21.9,10.5857,4,334,22,382.8,8.05,18.2 0.10659,80,1.91,0,0.413,5.936,19.5,10.5857,4,33
8.98296,0,18.1,1,0.77,6.212,97.4,2.1222,24,666,20.2,377.73,17.6,17.8 3.8497,0,18.1,1,0.77,6.395,91,2.5052,24,666,20.
5.20177,0,18.1,1,0.77,6.127,83.4,2.7227,24,666,20.2,395.43,11.48,22.7 4.26131,0,18.1,0,0.77,6.112,81.3,2.5091,24,666
4.54192,0,18.1,0,0.77,6.398,88,2.5182,24,666,20.2,374.56,7.79,25 3.83684,0,18.1,0,0.77,6.251,91.1,2.2955,24,666,20.2
3.67822,0,18.1,0,0.77,5.362,96.2,2.1036,24,666,20.2,380.79,10.19,20.8 4.22239,0,18.1,1,0.77,5.803,89,1.9047,24,666,2
3.47428,0,18.1,1,0.718,8.78,82.9,1.9047,24,666,20.2,354.55,5.29,21.9 4.55587,0,18.1,0,0.718,3.561,87.9,1.6132,24,666
4
3.69695,0,18.1,0,0.718,4.963,91.4,1.7523,24,666,20.2,316.03,14,21.9 13.5222,0,18.1,0,0.631,3.863,100,1.5106,24,666,2
4.89822,0,18.1,0,0.631,4.97,100,1.3325,24,666,20.2,375.52,3.26,50 5.66998,0,18.1,1,0.631,6.683,96.8,1.3567,24,666,20
6.53876,0,18.1,1,0.631,7.016,97.5,1.2024,24,666,20.2,392.05,2.96,50 9.2323,0,18.1,0,0.631,6.216,100,1.1691,24,666,2
8.26725,0,18.1,1,0.668,5.875,89.6,1.1296,24,666,20.2,347.88,8.88,50 11.1081,0,18.1,0,0.668,4.906,100,1.1742,24,666,
18.4982,0,18.1,0,0.668,4.138,100,1.137,24,666,20.2,396.9,37.97,13.8 19.6091,0,18.1,0,0.671,7.313,97.9,1.3163,24,666,
15.288,0,18.1,0,0.671,6.649,93.3,1.3449,24,666,20.2,363.02,23.24,13.9 9.82349,0,18.1,0,0.671,6.794,98.8,1.358,24,666
23.6482,0,18.1,0,0.671,6.38,96.2,1.3861,24,666,20.2,396.9,23.69,13.1 17.8667,0,18.1,0,0.671,6.223,100,1.3861,24,666,
88.9762,0,18.1,0,0.671,6.968,91.9,1.4165,24,666,20.2,396.9,17.21,10.4 15.8744,0,18.1,0,0.671,6.545,99.1,1.5192,24,66
9.18702,0,18.1,0,0.7,5.536,100,1.5804,24,666,20.2,396.9,23.6,11.3 7.99248,0,18.1,0,0.7,5.52,100,1.5331,24,666,20.2,3
20.0849,0,18.1,0,0.7,4.368,91.2,1.4395,24,666,20.2,285.83,30.63,8.8 16.8118,0,18.1,0,0.7,5.277,98.1,1.4261,24,666,20
24.3938,0,18.1,0,0.7,4.652,100,1.4672,24,666,20.2,396.9,28.28,10.5 22.5971,0,18.1,0,0.7,5,89.5,1.5184,24,666,20.2,39
14.3337,0,18.1,0,0.7,4.88,100,1.5895,24,666,20.2,372.92,30.62,10.2 8.15174,0,18.1,0,0.7,5.39,98.9,1.7281,24,666,20.2
6.96215,0,18.1,0,0.7,5.713,97,1.9265,24,666,20.2,394.43,17.11,15.1 5.29305,0,18.1,0,0.7,6.051,82.5,2.1678,24,666,20.
11.5779,0,18.1,0,0.7,5.036,97,1.77,24,666,20.2,396.9,25.68,9.7 8.64476,0,18.1,0,0.693,6.193,92.6,1.7912,24,666,20.2,3
13.3598,0,18.1,0,0.693,5.887,94.7,1.7821,24,666,20.2,396.9,16.35,12.7 8.71675,0,18.1,0,0.693,6.471,98.8,1.7257,24,66
5.87205,0,18.1,0,0.693,6.405,96,1.6768,24,666,20.2,396.9,19.37,12.5 7.67202,0,18.1,0,0.693,5.747,98.9,1.6334,24,666
38.3518,0,18.1,0,0.693,5.453,100,1.4896,24,666,20.2,396.9,30.59,5 9.91655,0,18.1,0,0.693,5.852,77.8,1.5004,24,666,20
25.0461,0,18.1,0,0.693,5.987,100,1.5888,24,666,20.2,396.9,26.77,5.6 14.2362,0,18.1,0,0.693,6.343,100,1.5741,24,666,2
9.59571,0,18.1,0,0.693,6.404,100,1.639,24,666,20.2,376.11,20.31,12.1 24.8017,0,18.1,0,0.693,5.349,96,1.7028,24,666,
41.5292,0,18.1,0,0.693,5.531,85.4,1.6074,24,666,20.2,329.46,27.38,8.5 67.9208,0,18.1,0,0.693,5.683,100,1.4254,24,666
20.7162,0,18.1,0,0.659,4.138,100,1.1781,24,666,20.2,370.22,23.34,11.9 11.9511,0,18.1,0,0.659,5.608,100,1.2852,24,66
7.40389,0,18.1,0,0.597,5.617,97.9,1.4547,24,666,20.2,314.64,26.4,17.2 14.4383,0,18.1,0,0.597,6.852,100,1.4655,24,666
51.1358,0,18.1,0,0.597,5.757,100,1.413,24,666,20.2,2.6,10.11,15 14.0507,0,18.1,0,0.597,6.657,100,1.5275,24,666,20.2
18.811,0,18.1,0,0.597,4.628,100,1.5539,24,666,20.2,28.79,34.37,17.9 28.6558,0,18.1,0,0.597,5.155,100,1.5894,24,666,2
45.7461,0,18.1,0,0.693,4.519,100,1.6582,24,666,20.2,88.27,36.98,7 18.0846,0,18.1,0,0.679,6.434,100,1.8347,24,666,20
10.8342,0,18.1,0,0.679,6.782,90.8,1.8195,24,666,20.2,21.57,25.79,7.5 25.9406,0,18.1,0,0.679,5.304,89.1,1.6475,24,666
73.5341,0,18.1,0,0.679,5.957,100,1.8026,24,666,20.2,16.45,20.62,8.8 11.8123,0,18.1,0,0.718,6.824,76.5,1.794,24,666,2
11.0874,0,18.1,0,0.718,6.411,100,1.8589,24,666,20.2,318.75,15.02,16.7 7.02259,0,18.1,0,0.718,6.006,95.3,1.8746,24,66
12.0482,0,18.1,0,0.614,5.648,87.6,1.9512,24,666,20.2,291.55,14.1,20.8 7.05042,0,18.1,0,0.614,6.103,85.1,2.0218,24,66
8.79212,0,18.1,0,0.584,5.565,70.6,2.0635,24,666,20.2,3.65,17.16,11.7 15.8603,0,18.1,0,0.679,5.896,95.4,1.9096,24,666
12.2472,0,18.1,0,0.584,5.837,59.7,1.9976,24,666,20.2,24.65,15.69,10.2 37.6619,0,18.1,0,0.679,6.202,78.7,1.8629,24,66
7.36711,0,18.1,0,0.679,6.193,78.1,1.9356,24,666,20.2,96.73,21.52,11 9.33889,0,18.1,0,0.679,6.38,95.6,1.9682,24,666,2
8.49213,0,18.1,0,0.584,6.348,86.1,2.0527,24,666,20.2,83.45,17.64,14.5 10.0623,0,18.1,0,0.584,6.833,94.3,2.0882,24,66
6.44405,0,18.1,0,0.584,6.425,74.8,2.2004,24,666,20.2,97.95,12.03,16.1 5.58107,0,18.1,0,0.713,6.436,87.9,2.3158,24,66
13.9134,0,18.1,0,0.713,6.208,95,2.2222,24,666,20.2,100.63,15.17,11.7 11.1604,0,18.1,0,0.74,6.629,94.6,2.1247,24,666,
14.4208,0,18.1,0,0.74,6.461,93.3,2.0026,24,666,20.2,27.49,18.05,9.6 15.1772,0,18.1,0,0.74,6.152,100,1.9142,24,666,20
13.6781,0,18.1,0,0.74,5.935,87.9,1.8206,24,666,20.2,68.95,34.02,8.4 9.39063,0,18.1,0,0.74,5.627,93.9,1.8172,24,666,2
22.0511,0,18.1,0,0.74,5.818,92.4,1.8662,24,666,20.2,391.45,22.11,10.5 9.72418,0,18.1,0,0.74,6.406,97.2,2.0651,24,666
5.66637,0,18.1,0,0.74,6.219,100,2.0048,24,666,20.2,395.69,16.59,18.4 9.96654,0,18.1,0,0.74,6.485,100,1.9784,24,666,
12.8023,0,18.1,0,0.74,5.854,96.6,1.8956,24,666,20.2,240.52,23.79,10.8 10.6718,0,18.1,0,0.74,6.459,94.8,1.9879,24,666
6.28807,0,18.1,0,0.74,6.341,96.4,2.072,24,666,20.2,318.01,17.79,14.9 9.92485,0,18.1,0,0.74,6.251,96.6,2.198,24,666,2
9.32909,0,18.1,0,0.713,6.185,98.7,2.2616,24,666,20.2,396.9,18.13,14.1 7.52601,0,18.1,0,0.713,6.417,98.3,2.185,24,666
6.71772,0,18.1,0,0.713,6.749,92.6,2.3236,24,666,20.2,0.32,17.44,13.4 5.44114,0,18.1,0,0.713,6.655,98.2,2.3552,24,666
5.09017,0,18.1,0,0.713,6.297,91.8,2.3682,24,666,20.2,385.09,17.27,16.1 8.24809,0,18.1,0,0.713,7.393,99.3,2.4527,24,6
9.51363,0,18.1,0,0.713,6.728,94.1,2.4961,24,666,20.2,6.68,18.71,14.9 4.75237,0,18.1,0,0.713,6.525,86.5,2.4358,24,666
4.66883,0,18.1,0,0.713,5.976,87.9,2.5806,24,666,20.2,10.48,19.01,12.7 8.20058,0,18.1,0,0.713,5.936,80.3,2.7792,24,66
5
7.75223,0,18.1,0,0.713,6.301,83.7,2.7831,24,666,20.2,272.21,16.23,14.9 6.80117,0,18.1,0,0.713,6.081,84.4,2.7175,24,6
4.81213,0,18.1,0,0.713,6.701,90,2.5975,24,666,20.2,255.23,16.42,16.4 3.69311,0,18.1,0,0.713,6.376,88.4,2.5671,24,666
6.65492,0,18.1,0,0.713,6.317,83,2.7344,24,666,20.2,396.9,13.99,19.5 5.82115,0,18.1,0,0.713,6.513,89.9,2.8016,24,666
7.83932,0,18.1,0,0.655,6.209,65.4,2.9634,24,666,20.2,396.9,13.22,21.4 3.1636,0,18.1,0,0.655,5.759,48.2,3.0665,24,666
3.77498,0,18.1,0,0.655,5.952,84.7,2.8715,24,666,20.2,22.01,17.15,19 4.42228,0,18.1,0,0.584,6.003,94.5,2.5403,24,666,
15.5757,0,18.1,0,0.58,5.926,71,2.9084,24,666,20.2,368.74,18.13,19.1 13.0751,0,18.1,0,0.58,5.713,56.7,2.8237,24,666,2
4.34879,0,18.1,0,0.58,6.167,84,3.0334,24,666,20.2,396.9,16.29,19.9 4.03841,0,18.1,0,0.532,6.229,90.7,3.0993,24,666,2
3.56868,0,18.1,0,0.58,6.437,75,2.8965,24,666,20.2,393.37,14.36,23.2 4.64689,0,18.1,0,0.614,6.98,67.6,2.5329,24,666,2
8.05579,0,18.1,0,0.584,5.427,95.4,2.4298,24,666,20.2,352.58,18.14,13.8 6.39312,0,18.1,0,0.584,6.162,97.4,2.206,24,66
4.87141,0,18.1,0,0.614,6.484,93.6,2.3053,24,666,20.2,396.21,18.68,16.7 15.0234,0,18.1,0,0.614,5.304,97.3,2.1007,24,6
10.233,0,18.1,0,0.614,6.185,96.7,2.1705,24,666,20.2,379.7,18.03,14.6 14.3337,0,18.1,0,0.614,6.229,88,1.9512,24,666,2
5.82401,0,18.1,0,0.532,6.242,64.7,3.4242,24,666,20.2,396.9,10.74,23 5.70818,0,18.1,0,0.532,6.75,74.9,3.3317,24,666,2
5.73116,0,18.1,0,0.532,7.061,77,3.4106,24,666,20.2,395.28,7.01,25 2.81838,0,18.1,0,0.532,5.762,40.3,4.0983,24,666,2
2.37857,0,18.1,0,0.583,5.871,41.9,3.724,24,666,20.2,370.73,13.34,20.6 3.67367,0,18.1,0,0.583,6.312,51.9,3.9917,24,66
5.69175,0,18.1,0,0.583,6.114,79.8,3.5459,24,666,20.2,392.68,14.98,19.1 4.83567,0,18.1,0,0.583,5.905,53.2,3.1523,24,6
0.15086,0,27.74,0,0.609,5.454,92.7,1.8209,4,711,20.1,395.09,18.06,15.2 0.18337,0,27.74,0,0.609,5.414,98.3,1.7554,4,7
0.20746,0,27.74,0,0.609,5.093,98,1.8226,4,711,20.1,318.43,29.68,8.1 0.10574,0,27.74,0,0.609,5.983,98.8,1.8681,4,711
0.11132,0,27.74,0,0.609,5.983,83.5,2.1099,4,711,20.1,396.9,13.35,20.1 0.17331,0,9.69,0,0.585,5.707,54,2.3817,6,391,1
0.27957,0,9.69,0,0.585,5.926,42.6,2.3817,6,391,19.2,396.9,13.59,24.5 0.17899,0,9.69,0,0.585,5.67,28.8,2.7986,6,391,1
0.2896,0,9.69,0,0.585,5.39,72.9,2.7986,6,391,19.2,396.9,21.14,19.7 0.26838,0,9.69,0,0.585,5.794,70.6,2.8927,6,391,19
0.23912,0,9.69,0,0.585,6.019,65.3,2.4091,6,391,19.2,396.9,12.92,21.2 0.17783,0,9.69,0,0.585,5.569,73.5,2.3999,6,391,
0.22438,0,9.69,0,0.585,6.027,79.7,2.4982,6,391,19.2,396.9,14.33,16.8 0.06263,0,11.93,0,0.573,6.593,69.1,2.4786,1,273
0.04527,0,11.93,0,0.573,6.12,76.7,2.2875,1,273,21,396.9,9.08,20.6 0.06076,0,11.93,0,0.573,6.976,91,2.1675,1,273,21,3
0.10959,0,11.93,0,0.573,6.794,89.3,2.3889,1,273,21,393.45,6.48,22 0.04741,0,11.93,0,0.573,6.03,80.8,2.505,1,273,21,3
6
Question 10 [1.5 pts] Please revise the MultiLayer NN Decision Boundary Notebook in the
Canvas to implement following tasks
• Generate a moon shaped dataset with two class lables (including 0.3 noise). Split the data into
60% training and 40% test data. Use 60% training data to train a neural network with 3 hidden
layer nodes. Show the training instances on the plot (color node into different colors, depending
on the lables). Also show the three lines corresponding to the three hidden nodes in the same
plot [0.5 pt]
• Retrain the network using 4 hidden nodes, and 5 hidden nodes, respectively. Show the four lines
corresponding to the four hidden nodes, and the five lines corresponding to the five hidden
nodes, respectively, on two separated plots (show the training instances on the same plot (color
node into different colors, depending on the labels)) [0.5 pt]
• Explain how does the neural network decision surface change, when increasing the number of
hidden nodes from 3, to 4, to 5. Explain what are the benefits and risk of increasing number of
hidden nodes, respectively [0.5 pt]
Question 11 [2 pts] The Multi-Layer NN Face Recognition Notebook in the Canvas shows detailed
procedures about how to use Oivetti face dataset (from AT&T) to train Neural Network classifiers for
face classification. The dataset in the Canvas also provides “olivetti_faces.npy” and
“olivetti_faces_target.npy”, which includes 400 faces in 40 classes (40 different person). Please
implement following face recognition task using Neural Networks.
•
Please show at least one face images for each class in the Oivetti face dataset100. Randomly
split the dataset into 60% training and 40% test samples. Train a one-hidden layer neural
network with 10 hidden nodes. Report the classification accuracy of the classifier on the test set
[1 pt]
•
Please use one time 10-fold cross validation to compare the performance of different neural
network architectures, including (1) one-hidden layer NN with 10 hidden nodes, (2) one-hidden
layer NN with 50 hidden nodes, (3) one-hidden layer NN with 500 hidden nodes, and (4) twohidden layer NN with 50 hidden nodes (1st layer) and 10 hidden nodes (2n layer). Please report
and compare the cross-validation accuracy of the four neural networks, and conclude which
classifier has the best performance [1 pt].
Question 12 [Extra Credit: 3 pts]
Please download IMDB50000.csv dataset from Canvas, and use a programming language
(Python, R, etc.) to implement tasks below. The IMDB50000.csv file includes 50,000 movie
reviews (from IMDB) and the sentiment (positive vs. negative) of the reviewer (there are 25,000
positive reviews and 25,000 negative reviews). Each review (each row) contains two parts. The
first column is the reviews (text), and the second column is the sentiment (positive or negative).
•
•
•
Read reviews from the IMDB50000.csv. Tokenize each review using space key, so each
review is represented as a set of tokens (words). Use the top 1,000 most frequent tokens
(words) as features to represent each review (so each review is represented as an instance
with 1000 features). The value of each feature is 1 if the view has the corresponding
token/word, or 0 otherwise. Use 1 as the label of the positive review, and 0 as the label of
the negative review (so each review is represented using 1,000 features and a class label).
Report the shape of your data frame, and use .head() to show the first several rows of the
data frame. [0.5 pt]
Randomly select 80% instances as training set, and the remaining 20% instances as test
set. Create a one hidden layer neural network (with 500 hidden nodes). Train the network
using training set, and validate the performance on the test set. Report the accuracy on the
test set. [0.5 pt]
Design one solution to improve the accuracy (which is better than the accuracy than step
2).
o Explain the motivation of your design (what motivate your design) [0.5 pt], the
implementation [0.5]
o Report the results of your new model. Use a plot to compare new model’s
accuracy vs. the accuracy from step 2 (must use same training and same test sets)
[0.5 pt].
o Explain any thoughts/changes you may consider to further improving your model
performance [0.5 pt]
o Hint for model design:
▪ You can consider using preprocessing to find better (more informative)
words. E.g., removing function words, such as “a”, “the”, “of”, removing
punctations etc.
▪ You can consider using information gain to find important features.
▪ You can consider using TF-IDF, instead of using 0/1 feature values
▪ You can consider changing your network structures, e.g., using two hidden
layer NN.
