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datos_2.mat
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datos_2.mat
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# Created by Octave 3.8.1, Wed Feb 04 00:50:12 2015 CST <bulletninja@bulletninja-laptop>
# name: P
# type: matrix
# rows: 5
# columns: 20
26 38 27 88 95 55 54 63 23 45 86 43 43 40 37 54 35 59 43 50
59 62 44 10 23 64 47 68 54 9 30 31 92 7 14 95 76 82 91 37
78 90 64 49 47 20 61 93 36 47 70 54 87 13 40 34 55 13 11 5
88 54 47 83 84 9 30 11 92 63 62 75 48 23 85 23 4 31 13 98
69 30 61 35 53 98 94 33 77 31 54 71 78 9 79 51 76 56 80 72
# name: difflb
# type: scalar
93
# name: diffub
# type: scalar
24
# name: lb
# type: scalar
1290
# name: mejoresvals
# type: matrix
# rows: 1
# columns: 30
1410 1400 1390 1400 1402 1422 1388 1383 1402 1399 1412 1412 1409 1383 1412 1396 1397 1412 1411 1383 1400 1408 1403 1398 1398 1390 1389 1422 1396 1394
# name: mejorindividuo
# type: matrix
# rows: 5
# columns: 20
43 54 27 35 95 55 88 43 50 23 26 54 45 37 86 43 59 63 40 38
31 47 44 76 23 64 10 91 37 54 59 95 9 14 30 92 82 68 7 62
54 61 64 55 47 20 49 11 5 36 78 34 47 40 70 87 13 93 13 90
75 30 47 4 84 9 83 13 98 92 88 23 63 85 62 48 31 11 23 54
71 94 61 76 53 98 35 80 72 77 69 51 31 79 54 78 56 33 9 30
# name: mejorval
# type: scalar
1383
# name: nfeval
# type: scalar
360
# name: relerrlb
# type: scalar
0.07209302325581396
# name: relerrub
# type: scalar
0.01766004415011038
# name: stats
# type: scalar struct
# ndims: 2
1 1
# length: 10
# name: errslb
# type: matrix
# rows: 25
# columns: 1
0
0
0
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0
0
0
0
0
0
0
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0
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0
# name: errsub
# type: matrix
# rows: 25
# columns: 1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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0
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0
0
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0
# name: avgerrlb
# type: scalar
0
# name: avgerrub
# type: scalar
0
# name: maxerrlb
# type: scalar
0
# name: maxerrub
# type: scalar
0
# name: minerrlb
# type: scalar
0
# name: minerrub
# type: scalar
0
# name: mederrlb
# type: scalar
0
# name: mederrub
# type: scalar
0
# name: ub
# type: scalar
1359
# name: vals
# type: matrix
# rows: 1
# columns: 30
1540.9 1539.4 1500.3 1500.3 1500.3 1496.1 1494.3 1494.3 1494.3 1491.9 1490.5 1490.5 1490.5 1490.5 1490.5 1488.95 1488.95 1469.2 1469.2 1466.05 1462.45 1462.45 1459.1 1456.85 1456.85 1456.85 1456.85 1456.85 1456.85 1433.735