Changeset 11613:1242f06bbdb4 in orange


Ignore:
Timestamp:
07/01/13 16:28:24 (10 months ago)
Author:
Ales Erjavec <ales.erjavec@…>
Branch:
default
Message:

Fixed changed regression tests output.

Files:
10 edited

Legend:

Unmodified
Added
Removed
  • Orange/testing/regression/results_reference/svm-custom-kernel.py.darwin.txt

    r10110 r11613  
    1 SVM - RBF(Euclidean) CA: 0.96 
    2 SVM - RBF(Hamming) CA: 0.886666666667 
     1SVM - RBF(Euclidean) CA: 0.97 
     2SVM - RBF(Hamming) CA: 0.87 
    33SVM - Composite CA: 0.94 
  • Orange/testing/regression/results_reference/svm-custom-kernel.py.txt

    r9954 r11613  
    1 SVM - RBF(Euclidean) CA: 0.966666666667 
    2 SVM - RBF(Hamming) CA: 0.873333333333 
     1SVM - RBF(Euclidean) CA: 0.97 
     2SVM - RBF(Hamming) CA: 0.87 
    33SVM - Composite CA: 0.94 
  • Orange/testing/regression/results_reference/svm-easy.py.txt

    r10435 r11613  
    11Name     CA        AUC 
    2 svm easy 0.83      0.96 
    3 svm      0.76      0.95 
     2svm easy 0.81      0.96 
     3svm      0.74      0.94 
  • Orange/testing/regression/results_reference/svm-linear-weights.py.txt

    r10586 r11613  
    1 ['0.0305391660', '0.0464525615', '0.0655766610', '0.1142851330', '0.1147435934', '0.1239657860', '0.1302437856', '0.1308238026', '0.1364165500', '0.1374175856', '0.1387632111', '0.1408812075', '0.1493575565', '0.1518344820', '0.1591399900', '0.1608572883', '0.1657731559', '0.1695697600', '0.1699370279', '0.1820761410', '0.1827041161', '0.1831093664', '0.1843390221', '0.1905684270', '0.1909180450', '0.1919806873', '0.1932982887', '0.2008838837', '0.2061566394', '0.2093389787', '0.2137991275', '0.2175498224', '0.2195202824', '0.2347380743', '0.2496567209', '0.2496831102', '0.2498289071', '0.2645926914', '0.2678048194', '0.2798043763', '0.3092300737', '0.3192185952', '0.3272979394', '0.3347197463', '0.3367415609', '0.3573783044', '0.3658304312', '0.3669869944', '0.3834953229', '0.3890995409', '0.4041756463', '0.4097605066', '0.4242536327', '0.4478969203', '0.4493259506', '0.4580637448', '0.4786304349', '0.4945177545', '0.5474717710', '0.5530522984', '0.5647568024', '0.5838555421', '0.5939775048', '0.5951921790', '0.5965606638', '0.6932491137', '0.6947063827', '0.7078091253', '0.8081597686', '0.8466186966', '0.8647671894', '0.9867498369', '1.0003215809', '1.0683522323', '1.2000832157', '1.4453028351', '1.9466576191', '2.2487957189', '3.2086625764'] 
     1['0.0305', '0.0464', '0.0656', '0.1143', '0.1147', '0.1240', '0.1303', '0.1308', '0.1364', '0.1374', '0.1388', '0.1409', '0.1493', '0.1519', '0.1592', '0.1609', '0.1658', '0.1695', '0.1699', '0.1821', '0.1827', '0.1831', '0.1843', '0.1906', '0.1909', '0.1920', '0.1933', '0.2008', '0.2062', '0.2094', '0.2138', '0.2175', '0.2195', '0.2347', '0.2496', '0.2497', '0.2499', '0.2646', '0.2679', '0.2797', '0.3093', '0.3193', '0.3273', '0.3347', '0.3367', '0.3573', '0.3658', '0.3671', '0.3835', '0.3890', '0.4042', '0.4099', '0.4243', '0.4478', '0.4493', '0.4581', '0.4786', '0.4945', '0.5475', '0.5531', '0.5647', '0.5839', '0.5939', '0.5953', '0.5966', '0.6932', '0.6946', '0.7078', '0.8082', '0.8466', '0.8647', '0.9868', '1.0003', '1.0684', '1.2001', '1.4453', '1.9466', '2.2487', '3.2087'] 
  • Orange/testing/regression/results_tests_20/modules_svm-custom-kernel.py.darwin.txt

    r10007 r11613  
    1 SVM - RBF(Euclidean) CA: 0.96 
    2 SVM - RBF(Hamming) CA: 0.886666666667 
     1SVM - RBF(Euclidean) CA: 0.97 
     2SVM - RBF(Hamming) CA: 0.87 
    33SVM - Composite CA: 0.94 
  • Orange/testing/regression/results_tests_20/modules_svm-custom-kernel.py.txt

    r9951 r11613  
    1 SVM - RBF(Euclidean) CA: 0.966666666667 
    2 SVM - RBF(Hamming) CA: 0.873333333333 
     1SVM - RBF(Euclidean) CA: 0.97 
     2SVM - RBF(Hamming) CA: 0.87 
    33SVM - Composite CA: 0.94 
  • Orange/testing/regression/results_tests_20/modules_svm-test.py.darwin.txt

    r10007 r11613  
    11           Name      CA     AUC 
    2 SVM - Linear      0.960   0.999 
     2SVM - Linear      0.967   0.999 
    33SVM - Poly        0.933   0.995 
    44SVM - RBF         0.967   0.999 
  • Orange/testing/regression/tests_20/modules_svm-custom-kernel.py

    r9952 r11613  
    2626tests=orngTest.crossValidation([l1, l2, l3], data, folds=5) 
    2727[ca1, ca2, ca3]=orngStat.CA(tests) 
    28 print l1.name, "CA:", ca1 
    29 print l2.name, "CA:", ca2 
    30 print l3.name, "CA:", ca3 
     28print l1.name, "CA: %.2f" % ca1 
     29print l2.name, "CA: %.2f" % ca2 
     30print l3.name, "CA: %.2f" % ca3 
  • docs/reference/rst/code/svm-custom-kernel.py

    r9889 r11613  
    3333[ca1, ca2, ca3] = evaluation.scoring.CA(tests) 
    3434 
    35 print l1.name, "CA:", ca1 
    36 print l2.name, "CA:", ca2 
    37 print l3.name, "CA:", ca3 
     35print l1.name, "CA: %.2f" % ca1 
     36print l2.name, "CA: %.2f" % ca2 
     37print l3.name, "CA: %.2f" % ca3 
  • docs/reference/rst/code/svm-linear-weights.py

    r10304 r11613  
    55classifier = svm.SVMLearner(brown, 
    66                            kernel_type=svm.kernels.Linear, 
    7                             normalization=False) 
     7                            normalization=False, 
     8                            eps=1e-9) 
    89 
    910weights = svm.get_linear_svm_weights(classifier) 
    10 print sorted("%.10f" % w for w in weights.values()) 
     11print sorted("%.4f" % w for w in weights.values()) 
    1112 
    1213import pylab as plt 
Note: See TracChangeset for help on using the changeset viewer.