ServerRun 38002
Creatorchuertas
ProgramLR-sbc-nbr f72
DatasetAxon Cars
Task typeMulticlassClassification
Created2y140d ago
Done! Flag_green
56m4s
251M
MulticlassClassification
55m36s
0.612
21s
0.826
9s

Log file

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   3.44055051e-01   4.82946987e-01   2.13801063e-01   6.51976210e-01
   4.37257701e-01   5.78172069e-01   8.61409178e-01   5.87721336e-01
   9.57027649e-02   3.61927272e-01   1.22547692e+00   9.20944290e-02
   2.15041131e-02   9.23985773e-01   4.01077065e-02   8.18983532e-01
   1.53350819e-01   5.93377460e-01   1.31350953e-01   1.63150517e-01
   3.75615500e-02   9.96836382e-02   4.62722217e-01   2.05023992e-01
   3.23195320e-01   1.47211211e-01   1.23743471e-01   3.73237478e-01
   9.39297195e-02   5.91199601e-01   2.10327291e-01   2.67564511e-01
   1.45773812e-02   7.37355374e-02   1.13226168e-03   4.40826789e-03
   6.55307073e-02   5.28726129e-01   1.24552580e-01   3.78844969e-01
   4.81604248e-01   2.23716517e-01   5.55198526e-02   2.29048095e-01
   5.48828693e-02   2.54891054e-02   6.00842877e-01   1.05481106e-02
   2.70684638e-01   6.09443026e-01   3.75450245e-01   5.41027668e-01
   3.01004591e-01   6.60601346e-02   6.27469382e-01   6.64474578e-01
   7.18241962e-01   1.64522798e+00   2.70684638e-01   3.19326445e-01
   5.39457667e-02   2.04842521e-01   6.85395843e-01   1.81586622e-01
   1.75695119e+00   5.40191133e-02   3.87564603e-01   1.01617596e+00
   2.66767135e-01]
lambs, mean: 0.00238537208838, var:2.0120964186e-05
mean lambda: 0.00238537208838
(100, 569)
b is [[ 0.10643939]
 [-0.11013418]
 [-0.52888454]
 [ 0.28650728]
 [ 0.05099502]
 [ 0.37847431]
 [ 0.10097586]
 [-0.21183248]
 [ 0.03979919]
 [-0.66307547]
 [ 0.01905097]
 [ 0.03646078]
 [-0.29109731]
 [ 0.27010158]
 [ 0.20031959]
 [ 0.20090737]
 [-0.42219007]
 [-0.34175417]
 [-0.10981689]
 [ 0.10512467]
 [-0.52097313]
 [-0.14800043]
 [-0.02048436]
 [-0.56894785]
 [-0.48898429]
 [ 0.14569846]
 [ 0.04334302]
 [ 0.27967896]
 [ 0.06728593]
 [-0.11031127]
 [ 0.10083748]
 [-0.1276429 ]
 [-0.22871155]
 [-0.78461166]
 [ 0.73787236]
 [ 0.00131077]
 [-0.59293924]
 [ 0.23089927]
 [ 0.62766565]
 [-0.37581355]
 [-0.12670316]
 [-0.06725311]
 [-0.2907017 ]
 [ 0.28922756]
 [ 0.32530102]
 [ 0.4912013 ]
 [ 0.04439624]
 [-0.09307179]
 [ 0.44278054]
 [ 0.06279411]
 [ 0.14722313]
 [-0.30349378]
 [ 0.3349127 ]
 [-0.69932454]
 [-0.00543729]
 [ 0.06887397]
 [ 0.31961879]
 [-0.12887626]
 [-0.18044688]
 [-0.10415728]
 [ 0.05730216]
 [-0.41615504]
 [-0.18156732]
 [-0.18709063]
 [-0.30276576]
 [-0.40632873]
 [-0.01855068]
 [-0.08946687]
 [ 0.39576052]
 [-0.21365616]
 [-0.08753903]
 [ 0.10362831]
 [-0.29847757]
 [-0.27310525]
 [ 0.61049242]
 [ 0.49252958]
 [ 0.33968286]
 [ 0.15289228]
 [-0.05406895]
 [ 0.75497726]
 [ 0.17627783]
 [-0.00351133]
 [ 0.25097636]
 [-0.02985332]
 [-0.02707467]
 [ 0.13819333]
 [ 0.21075137]
 [ 0.35811485]
 [-0.21251926]
 [-0.19931405]
 [ 0.68079527]
 [ 0.72224257]
 [ 0.20387162]
 [-0.066295  ]
 [-0.29145976]
 [-0.4274251 ]
 [-0.47507064]
 [ 0.36953531]
 [ 0.57458821]
 [-0.24172319]]
RUNNING THE L-BFGS-B CODE

           * * *

Machine precision = 1.084D-19
 N =        57000     M =           10
 This problem is unconstrained.

At X0         0 variables are exactly at the bounds

At iterate    0    f=  4.60630D+00    |proj g|=  4.58269D-03

At iterate   10    f=  3.21393D+00    |proj g|=  2.90841D-03

At iterate   20    f=  3.15713D+00    |proj g|=  1.52447D-03

At iterate   30    f=  3.14989D+00    |proj g|=  1.60881D-03

At iterate   40    f=  3.14842D+00    |proj g|=  8.48185D-05

At iterate   50    f=  3.14814D+00    |proj g|=  1.17266D-04

At iterate   60    f=  3.14806D+00    |proj g|=  7.93757D-05

At iterate   70    f=  3.14804D+00    |proj g|=  1.04620D-05

           * * *

Tit   = total number of iterations
Tnf   = total number of function evaluations
Tnint = total number of segments explored during Cauchy searches
Skip  = number of BFGS updates skipped
Nact  = number of active bounds at final generalized Cauchy point
Projg = norm of the final projected gradient
F     = final function value

           * * *

   N   Tit  Tnf  Tnint  Skip  Nact     Projg        F
57000   74   76      1     0     0   8.717D-06   3.148D+00
  F =   3.1480343915014393     

CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL            

 Cauchy                time 0.000E+00 seconds.
 Subspace minimization time 1.828E+00 seconds.
 Line search           time 1.861E+02 seconds.

 Total User time 1.912E+02 seconds.

=== END program1: ./run learn ../dataset2/train --- OK [3336s]

===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
d=72, n=14000 nd=1008000
datamatrix original dimension: (72, 14000)
datamatrix encoded dimension: (569, 14000)
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [21s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [2s]

===== MAIN: predict/evaluate on test data =====
=== START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in
=== END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
d=72, n=6000 nd=432000
datamatrix original dimension: (72, 6000)
datamatrix encoded dimension: (569, 6000)
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [9s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s]


real	56m9.180s
user	14m34.859s
sys	19m9.028s

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