Run 37939 |

Creator | chuertas |

Program | logreg-dis-python-sqrt |

Dataset | Axon Cars |

Task type | MulticlassClassification |

Created | 2y262d ago |

Done!

50m15s | |

250M | |

MulticlassClassification | |

49m47s | |

0.673 | |

21s | |

0.832 | |

9s |

#### Log file

===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train d=72, n=14000 nd=1008000 datamatrix original dimension: (72, 14000) using k=10 (72, 14000) (648, 14000) datamatrix encoded dimension: (569, 14000) mean lambda: 0.00238537208838 (100, 569) b is [[-0.2005605 ] [ 0.17070322] [ 0.02014761] [-0.23341866] [ 0.10768803] [ 0.00633504] [ 0.3923433 ] [-0.36699484] [-0.20860899] [-0.53472823] [-0.1456161 ] [-0.19409926] [-0.18695952] [ 0.14480488] [ 0.07188993] [ 0.04043204] [-0.33693411] [-0.10871814] [-0.00763506] [-0.11384675] [-0.31108321] [-0.3503754 ] [ 0.05646978] [-0.30229469] [-0.01733305] [ 0.56885649] [ 0.35812167] [ 0.30903815] [ 0.00486044] [-0.07814678] [ 0.42424593] [-0.07830464] [-0.31818425] [-0.32958972] [ 0.38411974] [ 0.01811869] [-0.54647106] [ 0.16429872] [-0.01005094] [-0.30417317] [ 0.35934597] [ 0.04894254] [-0.04043158] [ 0.36384402] [ 0.06069451] [ 0.17307907] [ 0.53771103] [-0.05121211] [ 0.20419557] [-0.08401672] [-0.10055749] [-0.01333571] [-0.14863891] [-0.50050928] [-0.17736913] [ 0.24526006] [-0.07222526] [-0.07475565] [-0.00820158] [-0.55315006] [ 0.19870736] [-0.10114486] [ 0.01038492] [ 0.14591256] [ 0.26919598] [-0.10788333] [ 0.43370994] [ 0.39539874] [ 0.31326477] [ 0.176643 ] [ 0.23650972] [-0.09622286] [ 0.20568077] [ 0.0423407 ] [ 0.09519258] [ 0.28400382] [ 0.18568316] [ 0.11019483] [-0.05053011] [ 0.11146987] [-0.03130594] [-0.15769316] [-0.10066102] [-0.02322682] [ 0.33977081] [ 0.03624295] [-0.18671066] [ 0.19050606] [-0.28927841] [-0.50813098] [ 0.07304354] [ 0.48487384] [ 0.02925162] [ 0.27323426] [-0.37097748] [-0.51624949] [-0.42966173] [ 0.33312309] [-0.00436366] [-0.12731425]] 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= 4.60635D+00 |proj g|= 3.94043D-03 At iterate 10 f= 3.73221D+00 |proj g|= 4.82893D-04 At iterate 20 f= 3.73054D+00 |proj g|= 1.41438D-04 * * * 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 29 32 1 0 0 5.494D-06 3.730D+00 F = 3.7303695639195240 CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL Cauchy time 0.000E+00 seconds. Subspace minimization time 5.640E-01 seconds. Line search time 7.714E+01 seconds. Total User time 8.025E+01 seconds. === END program1: ./run learn ../dataset2/train --- OK [2987s] ===== 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 [1s] === 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 [1s] ===== 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 [1s] === 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 [0s] real 50m20.674s user 11m53.857s sys 18m5.284s

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