This distribution has been tested as part of the cpan-testers
effort to test as many new uploads to CPAN as possible. See
http://testers.cpan.org/
Please cc any replies to cpan-testers@[EMAIL PROTECTED]
to keep other
test volunteers informed and to prevent any duplicate effort.
--
Dear VLADO,
This is a computer-generated error re****t created automatically by
CPANPLUS, version 0.84. Testers personal comments may appear
at the end of this re****t.
Thank you for uploading your work to CPAN. However, it appears that
there were some problems testing your distribution.
TEST RESULTS:
Below is the error stack from stage 'make test':
[MSG] [Sat Feb 2 02:17:07 2008] Trying to get
'http://www.cpan.org/authors/id/V/VL/VLADO/AI-NaiveBayes1-1.5.tar.gz'
[MSG] [Sat Feb 2 02:17:09 2008] Trying to get
'http://www.cpan.org/authors/id/V/VL/VLADO/CHECKSUMS'
[MSG] [Sat Feb 2 02:17:10 2008] Checksum matches for
'AI-NaiveBayes1-1.5.tar.gz'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/META.yml'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/MANIFEST'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/README'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted
'AI-NaiveBayes1-1.5/Makefile.PL'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/8-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/5.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/4-3.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted
'AI-NaiveBayes1-1.5/t/auxfunctions.pl'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/6-3.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/8.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/2.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/5-3.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/6-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/3-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/6-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/a2.arff'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/2-3.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/1-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/7.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/4-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/6.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/1.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/6-4.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/2-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/3-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/7-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/3.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/2-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/4.t'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/1-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/5-2.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/4-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/3-3.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/5-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/t/7-1.out'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted
'AI-NaiveBayes1-1.5/NaiveBayes1.pm'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI-NaiveBayes1-1.5/Changes'
[MSG] [Sat Feb 2 02:17:10 2008] Extracted 'AI::NaiveBayes1' to
'/opt/perl/testers/.cpanplus/5.8.8/build/AI-NaiveBayes1-1.5'
[MSG] [Sat Feb 2 02:17:11 2008] Checking if your kit is complete...
Looks good
Writing Makefile for AI::NaiveBayes1
[MSG] [Sat Feb 2 02:17:11 2008] DEFAULT 'filter_prereqs' HANDLER
RETURNING 'sub return value'
[MSG] [Sat Feb 2 02:17:12 2008] cp NaiveBayes1.pm
blib/lib/AI/NaiveBayes1.pm
Manifying blib/man3/AI::NaiveBayes1.3
[ERROR] [Sat Feb 2 02:17:18 2008] MAKE TEST failed:
不希望的裝置輸出入控制 (ioctl) t/1......Failed comparison with t/1-1.out!
Got: repairs=Y | H | 0.63157894736842
Expected: repairs=Y | H | 0.63157894736842
Got: repairs=Y | T | 0.36842105263157
Expected: repairs=Y | T | 0.36842105263157
Got: repairs=N | H | 0.20967741935483
Expected: repairs=N | H | 0.20967741935483
Got: repairs=N | T | 0.79032258064516
Expected: repairs=N | T | 0.79032258064516
Got: repairs=Y | B | 0.68421052631578
Expected: repairs=Y | B | 0.68421052631578
Got: repairs=Y | N | 0.31578947368421
Expected: repairs=Y | N | 0.31578947368421
Got: repairs=N | B | 0.19354838709677
Expected: repairs=N | B | 0.19354838709677
Got: repairs=N | N | 0.80645161290322
Expected: repairs=N | N | 0.80645161290322
# Failed test at t/auxfunctions.pl line 17.
# Failed test at t/1.t line 38.
# got: 'Model:
# category | P(category)
# ----------+-------------
# repairs=Y | 0.38
# repairs=N | 0.62
# ----------+-------------
#
# category | model | P( model | category )
# ----------+-------+-----------------------
# repairs=Y | H | 0.63157894736842
# repairs=Y | T | 0.36842105263157
# ----------+-------+-----------------------
# repairs=N | H | 0.20967741935483
# repairs=N | T | 0.79032258064516
# ----------+-------+-----------------------
#
# category | place | P( place | category )
# ----------+-------+-----------------------
# repairs=Y | B | 0.68421052631578
# repairs=Y | N | 0.31578947368421
# ----------+-------+-----------------------
# repairs=N | B | 0.19354838709677
# repairs=N | N | 0.80645161290322
# ----------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ----------+-------------
# repairs=Y | 0.38
# repairs=N | 0.62
# ----------+-------------
#
# category | model | P( model | category )
# ----------+-------+-----------------------
# repairs=Y | H | 0.63157894736842
# repairs=Y | T | 0.36842105263157
# ----------+-------+-----------------------
# repairs=N | H | 0.20967741935483
# repairs=N | T | 0.79032258064516
# ----------+-------+-----------------------
#
# category | place | P( place | category )
# ----------+-------+-----------------------
# repairs=Y | B | 0.68421052631578
# repairs=Y | N | 0.31578947368421
# ----------+-------+-----------------------
# repairs=N | B | 0.19354838709677
# repairs=N | N | 0.80645161290322
# ----------+-------+-----------------------
#
# '
# Failed test at t/1.t line 43.
# got: 'Model:
# category | P(category)
# ----------+-------------
# repairs=Y | 0.38
# repairs=N | 0.62
# ----------+-------------
#
# category | model | P( model | category )
# ----------+-------+-----------------------
# repairs=Y | H | 0.63157894736842
# repairs=Y | T | 0.36842105263157
# ----------+-------+-----------------------
# repairs=N | H | 0.20967741935483
# repairs=N | T | 0.79032258064516
# ----------+-------+-----------------------
#
# category | place | P( place | category )
# ----------+-------+-----------------------
# repairs=Y | B | 0.68421052631578
# repairs=Y | N | 0.31578947368421
# ----------+-------+-----------------------
# repairs=N | B | 0.19354838709677
# repairs=N | N | 0.80645161290322
# ----------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ----------+-------------
# repairs=Y | 0.38
# repairs=N | 0.62
# ----------+-------------
#
# category | model | P( model | category )
# ----------+-------+-----------------------
# repairs=Y | H | 0.63157894736842
# repairs=Y | T | 0.36842105263157
# ----------+-------+-----------------------
# repairs=N | H | 0.20967741935483
# repairs=N | T | 0.79032258064516
# ----------+-------+-----------------------
#
# category | place | P( place | category )
# ----------+-------+-----------------------
# repairs=Y | B | 0.68421052631578
# repairs=Y | N | 0.31578947368421
# ----------+-------+-----------------------
# repairs=N | B | 0.19354838709677
# repairs=N | N | 0.80645161290322
# ----------+-------+-----------------------
#
# '
# Looks like you failed 3 tests of 4.
Dubious, test returned 3 (wstat 768, 0x300)
Failed 3/4 subtests
t/2......
# Failed test at t/2.t line 65.
# got: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+-----------------------
# spam=N | N | 0.666666666666666667
# spam=N | Y | 0.333333333333333333
# ---------+------+-----------------------
# spam=Y | N | 0.0588235294117647059
# spam=Y | Y | 0.941176470588235294
# ---------+------+-----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333333
# spam=N | Y | 0.666666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529411765
# spam=Y | Y | 0.352941176470588235
# ---------+---------+-------------------------
#
# category | size1 | P( size1 | category )
# ---------+-------+-----------------------
# spam=N | L | 0.333333333333333333
# spam=N | S | 0.666666666666666667
# ---------+-------+-----------------------
# spam=Y | L | 0.588235294117647059
# spam=Y | S | 0.411764705882352941
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+----------------------
# spam=N | N | 0.666666666666667
# spam=N | Y | 0.333333333333333
# ---------+------+----------------------
# spam=Y | N | 0.0588235294117647
# spam=Y | Y | 0.941176470588235
# ---------+------+----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333
# spam=N | Y | 0.666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529412
# spam=Y | Y | 0.352941176470588
# ---------+---------+-------------------------
#
# category | size1 | P( size1 | category )
# ---------+-------+-----------------------
# spam=N | L | 0.333333333333333
# spam=N | S | 0.666666666666667
# ---------+-------+-----------------------
# spam=Y | L | 0.588235294117647
# spam=Y | S | 0.411764705882353
# ---------+-------+-----------------------
#
# '
# Failed test at t/2.t line 75.
# got: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+-----------------------
# spam=N | N | 0.666666666666666667
# spam=N | Y | 0.333333333333333333
# ---------+------+-----------------------
# spam=Y | N | 0.0588235294117647059
# spam=Y | Y | 0.941176470588235294
# ---------+------+-----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333333
# spam=N | Y | 0.666666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529411765
# spam=Y | Y | 0.352941176470588235
# ---------+---------+-------------------------
#
# category | size1 | P( size1 | category )
# ---------+-------+-----------------------
# spam=N | L | 0.333333333333333333
# spam=N | S | 0.666666666666666667
# ---------+-------+-----------------------
# spam=Y | L | 0.588235294117647059
# spam=Y | S | 0.411764705882352941
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+----------------------
# spam=N | N | 0.666666666666667
# spam=N | Y | 0.333333333333333
# ---------+------+----------------------
# spam=Y | N | 0.0588235294117647
# spam=Y | Y | 0.941176470588235
# ---------+------+----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333
# spam=N | Y | 0.666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529412
# spam=Y | Y | 0.352941176470588
# ---------+---------+-------------------------
#
# category | size1 | P( size1 | category )
# ---------+-------+-----------------------
# spam=N | L | 0.333333333333333
# spam=N | S | 0.666666666666667
# ---------+-------+-----------------------
# spam=Y | L | 0.588235294117647
# spam=Y | S | 0.411764705882353
# ---------+-------+-----------------------
#
# '
# Failed test at t/2.t line 79.
# got: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+-----------------------
# spam=N | N | 0.666666666666666667
# spam=N | Y | 0.333333333333333333
# ---------+------+-----------------------
# spam=Y | N | 0.0588235294117647059
# spam=Y | Y | 0.941176470588235294
# ---------+------+-----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333333
# spam=N | Y | 0.666666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529411765
# spam=Y | Y | 0.352941176470588235
# ---------+---------+-------------------------
#
# category | size1 | P( size1 | category )
# ---------+-------+-----------------------
# spam=N | L | 0.333333333333333333
# spam=N | S | 0.666666666666666667
# ---------+-------+-----------------------
# spam=Y | L | 0.588235294117647059
# spam=Y | S | 0.411764705882352941
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+----------------------
# spam=N | N | 0.666666666666667
# spam=N | Y | 0.333333333333333
# ---------+------+----------------------
# spam=Y | N | 0.0588235294117647
# spam=Y | Y | 0.941176470588235
# ---------+------+----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333
# spam=N | Y | 0.666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529412
# spam=Y | Y | 0.352941176470588
# ---------+---------+-------------------------
#
# category | size1 | P( size1 | category )
# ---------+-------+-----------------------
# spam=N | L | 0.333333333333333
# spam=N | S | 0.666666666666667
# ---------+-------+-----------------------
# spam=Y | L | 0.588235294117647
# spam=Y | S | 0.411764705882353
# ---------+-------+-----------------------
#
# '
# Looks like you failed 3 tests of 6.
Dubious, test returned 3 (wstat 768, 0x300)
Failed 3/6 subtests
t/3......
# Failed test at t/3.t line 57.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# play=no | 0.357142857142857143
# play=yes | 0.642857142857142857
# ---------+----------------------
#
# category | humidity | P( humidity | category )
# ---------+----------+--------------------------
# play=no | high | 0.8
# play=no | normal | 0.2
# ---------+----------+--------------------------
# play=yes | high | 0.333333333333333333
# play=yes | normal | 0.666666666666666667
# ---------+----------+--------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444444
# play=yes | rainy | 0.333333333333333333
# play=yes | sunny | 0.222222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+-----------------------------
# play=no | cool | 0.2
# play=no | hot | 0.4
# play=no | mild | 0.4
# ---------+-------------+-----------------------------
# play=yes | cool | 0.333333333333333333
# play=yes | hot | 0.222222222222222222
# play=yes | mild | 0.444444444444444444
# ---------+-------------+-----------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666666667
# play=yes | TRUE | 0.333333333333333333
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# play=no | 0.357142857142857
# play=yes | 0.642857142857143
# ---------+-------------------
#
# category | humidity | P( humidity | category )
# ---------+----------+--------------------------
# play=no | high | 0.8
# play=no | normal | 0.2
# ---------+----------+--------------------------
# play=yes | high | 0.333333333333333
# play=yes | normal | 0.666666666666667
# ---------+----------+--------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444
# play=yes | rainy | 0.333333333333333
# play=yes | sunny | 0.222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+-----------------------------
# play=no | cool | 0.2
# play=no | hot | 0.4
# play=no | mild | 0.4
# ---------+-------------+-----------------------------
# play=yes | cool | 0.333333333333333
# play=yes | hot | 0.222222222222222
# play=yes | mild | 0.444444444444444
# ---------+-------------+-----------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666667
# play=yes | TRUE | 0.333333333333333
# ---------+-------+-----------------------
#
# '
# Failed test at t/3.t line 67.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# play=no | 0.357142857142857143
# play=yes | 0.642857142857142857
# ---------+----------------------
#
# category | humidity | P( humidity | category )
# ---------+----------+--------------------------
# play=no | high | 0.8
# play=no | normal | 0.2
# ---------+----------+--------------------------
# play=yes | high | 0.333333333333333333
# play=yes | normal | 0.666666666666666667
# ---------+----------+--------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444444
# play=yes | rainy | 0.333333333333333333
# play=yes | sunny | 0.222222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+-----------------------------
# play=no | cool | 0.2
# play=no | hot | 0.4
# play=no | mild | 0.4
# ---------+-------------+-----------------------------
# play=yes | cool | 0.333333333333333333
# play=yes | hot | 0.222222222222222222
# play=yes | mild | 0.444444444444444444
# ---------+-------------+-----------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666666667
# play=yes | TRUE | 0.333333333333333333
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# play=no | 0.357142857142857
# play=yes | 0.642857142857143
# ---------+-------------------
#
# category | humidity | P( humidity | category )
# ---------+----------+--------------------------
# play=no | high | 0.8
# play=no | normal | 0.2
# ---------+----------+--------------------------
# play=yes | high | 0.333333333333333
# play=yes | normal | 0.666666666666667
# ---------+----------+--------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444
# play=yes | rainy | 0.333333333333333
# play=yes | sunny | 0.222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+-----------------------------
# play=no | cool | 0.2
# play=no | hot | 0.4
# play=no | mild | 0.4
# ---------+-------------+-----------------------------
# play=yes | cool | 0.333333333333333
# play=yes | hot | 0.222222222222222
# play=yes | mild | 0.444444444444444
# ---------+-------------+-----------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666667
# play=yes | TRUE | 0.333333333333333
# ---------+-------+-----------------------
#
# '
# Failed test at t/3.t line 71.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# play=no | 0.357142857142857143
# play=yes | 0.642857142857142857
# ---------+----------------------
#
# category | humidity | P( humidity | category )
# ---------+----------+--------------------------
# play=no | high | 0.8
# play=no | normal | 0.2
# ---------+----------+--------------------------
# play=yes | high | 0.333333333333333333
# play=yes | normal | 0.666666666666666667
# ---------+----------+--------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444444
# play=yes | rainy | 0.333333333333333333
# play=yes | sunny | 0.222222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+-----------------------------
# play=no | cool | 0.2
# play=no | hot | 0.4
# play=no | mild | 0.4
# ---------+-------------+-----------------------------
# play=yes | cool | 0.333333333333333333
# play=yes | hot | 0.222222222222222222
# play=yes | mild | 0.444444444444444444
# ---------+-------------+-----------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666666667
# play=yes | TRUE | 0.333333333333333333
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# play=no | 0.357142857142857
# play=yes | 0.642857142857143
# ---------+-------------------
#
# category | humidity | P( humidity | category )
# ---------+----------+--------------------------
# play=no | high | 0.8
# play=no | normal | 0.2
# ---------+----------+--------------------------
# play=yes | high | 0.333333333333333
# play=yes | normal | 0.666666666666667
# ---------+----------+--------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444
# play=yes | rainy | 0.333333333333333
# play=yes | sunny | 0.222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+-----------------------------
# play=no | cool | 0.2
# play=no | hot | 0.4
# play=no | mild | 0.4
# ---------+-------------+-----------------------------
# play=yes | cool | 0.333333333333333
# play=yes | hot | 0.222222222222222
# play=yes | mild | 0.444444444444444
# ---------+-------------+-----------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666667
# play=yes | TRUE | 0.333333333333333
# ---------+-------+-----------------------
#
# '
# Looks like you failed 3 tests of 6.
Dubious, test returned 3 (wstat 768, 0x300)
Failed 3/6 subtests
t/4......
# Failed test at t/4.t line 60.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# play=no | 0.357142857142857143
# play=yes | 0.642857142857142857
# ---------+----------------------
#
# category | humidity | P( humidity | category )
#
---------+----------+---------------------------------------------------------------
# play=no | real | Gaussian(mean=86.2,stddev=9.73139250056229106)
#
---------+----------+---------------------------------------------------------------
# play=yes | real |
Gaussian(mean=79.1111111111111111,stddev=10.2157286138146363)
#
---------+----------+---------------------------------------------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444444
# play=yes | rainy | 0.333333333333333333
# play=yes | sunny | 0.222222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+------------------------------------------------
# play=no | real | Gaussian(mean=74.6,stddev=7.89303490426844622)
# ---------+-------------+------------------------------------------------
# play=yes | real | Gaussian(mean=73,stddev=6.16441400296897645)
# ---------+-------------+------------------------------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666666667
# play=yes | TRUE | 0.333333333333333333
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# play=no | 0.357142857142857
# play=yes | 0.642857142857143
# ---------+-------------------
#
# category | humidity | P( humidity | category )
#
---------+----------+---------------------------------------------------------
# play=no | real | Gaussian(mean=86.2,stddev=9.73139250056229)
#
---------+----------+---------------------------------------------------------
# play=yes | real |
Gaussian(mean=79.1111111111111,stddev=10.2157286138146)
#
---------+----------+---------------------------------------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444
# play=yes | rainy | 0.333333333333333
# play=yes | sunny | 0.222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+---------------------------------------------
# play=no | real | Gaussian(mean=74.6,stddev=7.89303490426845)
# ---------+-------------+---------------------------------------------
# play=yes | real | Gaussian(mean=73,stddev=6.16441400296898)
# ---------+-------------+---------------------------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666667
# play=yes | TRUE | 0.333333333333333
# ---------+-------+-----------------------
#
# '
# Failed test at t/4.t line 70.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# play=no | 0.357142857142857143
# play=yes | 0.642857142857142857
# ---------+----------------------
#
# category | humidity | P( humidity | category )
#
---------+----------+---------------------------------------------------------------
# play=no | real | Gaussian(mean=86.2,stddev=9.73139250056229106)
#
---------+----------+---------------------------------------------------------------
# play=yes | real |
Gaussian(mean=79.1111111111111111,stddev=10.2157286138146363)
#
---------+----------+---------------------------------------------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444444
# play=yes | rainy | 0.333333333333333333
# play=yes | sunny | 0.222222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+------------------------------------------------
# play=no | real | Gaussian(mean=74.6,stddev=7.89303490426844622)
# ---------+-------------+------------------------------------------------
# play=yes | real | Gaussian(mean=73,stddev=6.16441400296897645)
# ---------+-------------+------------------------------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666666667
# play=yes | TRUE | 0.333333333333333333
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# play=no | 0.357142857142857
# play=yes | 0.642857142857143
# ---------+-------------------
#
# category | humidity | P( humidity | category )
#
---------+----------+---------------------------------------------------------
# play=no | real | Gaussian(mean=86.2,stddev=9.73139250056229)
#
---------+----------+---------------------------------------------------------
# play=yes | real |
Gaussian(mean=79.1111111111111,stddev=10.2157286138146)
#
---------+----------+---------------------------------------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444
# play=yes | rainy | 0.333333333333333
# play=yes | sunny | 0.222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+---------------------------------------------
# play=no | real | Gaussian(mean=74.6,stddev=7.89303490426845)
# ---------+-------------+---------------------------------------------
# play=yes | real | Gaussian(mean=73,stddev=6.16441400296898)
# ---------+-------------+---------------------------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666667
# play=yes | TRUE | 0.333333333333333
# ---------+-------+-----------------------
#
# '
# Failed test at t/4.t line 74.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# play=no | 0.357142857142857143
# play=yes | 0.642857142857142857
# ---------+----------------------
#
# category | humidity | P( humidity | category )
#
---------+----------+---------------------------------------------------------------
# play=no | real | Gaussian(mean=86.2,stddev=9.73139250056229106)
#
---------+----------+---------------------------------------------------------------
# play=yes | real |
Gaussian(mean=79.1111111111111111,stddev=10.2157286138146363)
#
---------+----------+---------------------------------------------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444444
# play=yes | rainy | 0.333333333333333333
# play=yes | sunny | 0.222222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+------------------------------------------------
# play=no | real | Gaussian(mean=74.6,stddev=7.89303490426844622)
# ---------+-------------+------------------------------------------------
# play=yes | real | Gaussian(mean=73,stddev=6.16441400296897645)
# ---------+-------------+------------------------------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666666667
# play=yes | TRUE | 0.333333333333333333
# ---------+-------+-----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# play=no | 0.357142857142857
# play=yes | 0.642857142857143
# ---------+-------------------
#
# category | humidity | P( humidity | category )
#
---------+----------+---------------------------------------------------------
# play=no | real | Gaussian(mean=86.2,stddev=9.73139250056229)
#
---------+----------+---------------------------------------------------------
# play=yes | real |
Gaussian(mean=79.1111111111111,stddev=10.2157286138146)
#
---------+----------+---------------------------------------------------------
#
# category | outlook | P( outlook | category )
# ---------+----------+-------------------------
# play=no | rainy | 0.4
# play=no | sunny | 0.6
# ---------+----------+-------------------------
# play=yes | overcast | 0.444444444444444
# play=yes | rainy | 0.333333333333333
# play=yes | sunny | 0.222222222222222
# ---------+----------+-------------------------
#
# category | temperature | P( temperature | category )
# ---------+-------------+---------------------------------------------
# play=no | real | Gaussian(mean=74.6,stddev=7.89303490426845)
# ---------+-------------+---------------------------------------------
# play=yes | real | Gaussian(mean=73,stddev=6.16441400296898)
# ---------+-------------+---------------------------------------------
#
# category | windy | P( windy | category )
# ---------+-------+-----------------------
# play=no | FALSE | 0.4
# play=no | TRUE | 0.6
# ---------+-------+-----------------------
# play=yes | FALSE | 0.666666666666667
# play=yes | TRUE | 0.333333333333333
# ---------+-------+-----------------------
#
# '
# Looks like you failed 3 tests of 6.
Dubious, test returned 3 (wstat 768, 0x300)
Failed 3/6 subtests
t/5......
# Failed test at t/5.t line 66.
# got: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+-----------------------
# spam=N | N | 0.666666666666666667
# spam=N | Y | 0.333333333333333333
# ---------+------+-----------------------
# spam=Y | N | 0.0588235294117647059
# spam=Y | Y | 0.941176470588235294
# ---------+------+-----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333333
# spam=N | Y | 0.666666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529411765
# spam=Y | Y | 0.352941176470588235
# ---------+---------+-------------------------
#
# category | size | P( size | category )
#
---------+------+---------------------------------------------------------------
# spam=N | real |
Gaussian(mean=1443.33333333333333,stddev=1521.30777074638429)
#
---------+------+---------------------------------------------------------------
# spam=Y | real |
Gaussian(mean=2344.64705882352941,stddev=1397.40106721265203)
#
---------+------+---------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+----------------------
# spam=N | N | 0.666666666666667
# spam=N | Y | 0.333333333333333
# ---------+------+----------------------
# spam=Y | N | 0.0588235294117647
# spam=Y | Y | 0.941176470588235
# ---------+------+----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333
# spam=N | Y | 0.666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529412
# spam=Y | Y | 0.352941176470588
# ---------+---------+-------------------------
#
# category | size | P( size | category )
#
---------+------+---------------------------------------------------------
# spam=N | real |
Gaussian(mean=1443.33333333333,stddev=1521.30777074638)
#
---------+------+---------------------------------------------------------
# spam=Y | real |
Gaussian(mean=2344.64705882353,stddev=1397.40106721265)
#
---------+------+---------------------------------------------------------
#
# '
# Failed test at t/5.t line 76.
# got: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+-----------------------
# spam=N | N | 0.666666666666666667
# spam=N | Y | 0.333333333333333333
# ---------+------+-----------------------
# spam=Y | N | 0.0588235294117647059
# spam=Y | Y | 0.941176470588235294
# ---------+------+-----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333333
# spam=N | Y | 0.666666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529411765
# spam=Y | Y | 0.352941176470588235
# ---------+---------+-------------------------
#
# category | size | P( size | category )
#
---------+------+---------------------------------------------------------------
# spam=N | real |
Gaussian(mean=1443.33333333333333,stddev=1521.30777074638429)
#
---------+------+---------------------------------------------------------------
# spam=Y | real |
Gaussian(mean=2344.64705882352941,stddev=1397.40106721265203)
#
---------+------+---------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+----------------------
# spam=N | N | 0.666666666666667
# spam=N | Y | 0.333333333333333
# ---------+------+----------------------
# spam=Y | N | 0.0588235294117647
# spam=Y | Y | 0.941176470588235
# ---------+------+----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333
# spam=N | Y | 0.666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529412
# spam=Y | Y | 0.352941176470588
# ---------+---------+-------------------------
#
# category | size | P( size | category )
#
---------+------+---------------------------------------------------------
# spam=N | real |
Gaussian(mean=1443.33333333333,stddev=1521.30777074638)
#
---------+------+---------------------------------------------------------
# spam=Y | real |
Gaussian(mean=2344.64705882353,stddev=1397.40106721265)
#
---------+------+---------------------------------------------------------
#
# '
# Failed test at t/5.t line 80.
# got: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+-----------------------
# spam=N | N | 0.666666666666666667
# spam=N | Y | 0.333333333333333333
# ---------+------+-----------------------
# spam=Y | N | 0.0588235294117647059
# spam=Y | Y | 0.941176470588235294
# ---------+------+-----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333333
# spam=N | Y | 0.666666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529411765
# spam=Y | Y | 0.352941176470588235
# ---------+---------+-------------------------
#
# category | size | P( size | category )
#
---------+------+---------------------------------------------------------------
# spam=N | real |
Gaussian(mean=1443.33333333333333,stddev=1521.30777074638429)
#
---------+------+---------------------------------------------------------------
# spam=Y | real |
Gaussian(mean=2344.64705882352941,stddev=1397.40106721265203)
#
---------+------+---------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# spam=N | 0.15
# spam=Y | 0.85
# ---------+-------------
#
# category | html | P( html | category )
# ---------+------+----------------------
# spam=N | N | 0.666666666666667
# spam=N | Y | 0.333333333333333
# ---------+------+----------------------
# spam=Y | N | 0.0588235294117647
# spam=Y | Y | 0.941176470588235
# ---------+------+----------------------
#
# category | morning | P( morning | category )
# ---------+---------+-------------------------
# spam=N | N | 0.333333333333333
# spam=N | Y | 0.666666666666667
# ---------+---------+-------------------------
# spam=Y | N | 0.647058823529412
# spam=Y | Y | 0.352941176470588
# ---------+---------+-------------------------
#
# category | size | P( size | category )
#
---------+------+---------------------------------------------------------
# spam=N | real |
Gaussian(mean=1443.33333333333,stddev=1521.30777074638)
#
---------+------+---------------------------------------------------------
# spam=Y | real |
Gaussian(mean=2344.64705882353,stddev=1397.40106721265)
#
---------+------+---------------------------------------------------------
#
# '
# Looks like you failed 3 tests of 6.
Dubious, test returned 3 (wstat 768, 0x300)
Failed 3/6 subtests
t/6......
# Failed test at t/6.t line 24.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
# ---------+---+----------------------
# S=Y | 0 | 0.315789473684210526
# S=Y | 2 | 0.684210526315789474
# ---------+---+----------------------
# S=N | 0 | 0.806451612903225806
# S=N | 2 | 0.193548387096774194
# ---------+---+----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
# ---------+---+-------------------
# S=Y | 0 | 0.315789473684211
# S=Y | 2 | 0.684210526315789
# ---------+---+-------------------
# S=N | 0 | 0.806451612903226
# S=N | 2 | 0.193548387096774
# ---------+---+-------------------
#
# '
# Failed test at t/6.t line 32.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
# ---------+---+----------------------
# S=Y | 0 | 0.315789473684210526
# S=Y | 2 | 0.684210526315789474
# ---------+---+----------------------
# S=N | 0 | 0.806451612903225806
# S=N | 2 | 0.193548387096774194
# ---------+---+----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
# ---------+---+-------------------
# S=Y | 0 | 0.315789473684211
# S=Y | 2 | 0.684210526315789
# ---------+---+-------------------
# S=N | 0 | 0.806451612903226
# S=N | 2 | 0.193548387096774
# ---------+---+-------------------
#
# '
# Failed test at t/6.t line 59.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263157895,stddev=0.935836242984962902)
#
---------+------+-----------------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548387,stddev=0.793363503758019253)
#
---------+------+-----------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263158,stddev=0.935836242984963)
#
---------+------+-----------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548,stddev=0.793363503758019)
#
---------+------+-----------------------------------------------------------
#
# '
# Failed test at t/6.t line 64.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263157895,stddev=0.935836242984962902)
#
---------+------+-----------------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548387,stddev=0.793363503758019253)
#
---------+------+-----------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263158,stddev=0.935836242984963)
#
---------+------+-----------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548,stddev=0.793363503758019)
#
---------+------+-----------------------------------------------------------
#
# '
# Looks like you failed 4 tests of 9.
Dubious, test returned 4 (wstat 1024, 0x400)
Failed 4/9 subtests
t/7......
# Failed test at t/7.t line 24.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
# ---------+---+----------------------
# S=Y | 0 | 0.315789473684210526
# S=Y | 2 | 0.684210526315789474
# ---------+---+----------------------
# S=N | 0 | 0.806451612903225806
# S=N | 2 | 0.193548387096774194
# ---------+---+----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
# ---------+---+-------------------
# S=Y | 0 | 0.315789473684211
# S=Y | 2 | 0.684210526315789
# ---------+---+-------------------
# S=N | 0 | 0.806451612903226
# S=N | 2 | 0.193548387096774
# ---------+---+-------------------
#
# '
# Failed test at t/7.t line 32.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
# ---------+---+----------------------
# S=Y | 0 | 0.315789473684210526
# S=Y | 2 | 0.684210526315789474
# ---------+---+----------------------
# S=N | 0 | 0.806451612903225806
# S=N | 2 | 0.193548387096774194
# ---------+---+----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
# ---------+---+-------------------
# S=Y | 0 | 0.315789473684211
# S=Y | 2 | 0.684210526315789
# ---------+---+-------------------
# S=N | 0 | 0.806451612903226
# S=N | 2 | 0.193548387096774
# ---------+---+-------------------
#
# '
# Failed test at t/7.t line 64.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263157895,stddev=0.935836242984962902)
#
---------+------+-----------------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548387,stddev=0.793363503758019253)
#
---------+------+-----------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263158,stddev=0.935836242984963)
#
---------+------+-----------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548,stddev=0.793363503758019)
#
---------+------+-----------------------------------------------------------
#
# '
# Failed test at t/7.t line 69.
# got: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+----------------------
# S=Y | N | 0.368421052631578947
# S=Y | Y | 0.631578947368421053
# ---------+---+----------------------
# S=N | N | 0.79032258064516129
# S=N | Y | 0.20967741935483871
# ---------+---+----------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263157895,stddev=0.935836242984962902)
#
---------+------+-----------------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548387,stddev=0.793363503758019253)
#
---------+------+-----------------------------------------------------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------
# S=Y | 0.38
# S=N | 0.62
# ---------+-------------
#
# category | C | P( C | category )
# ---------+---+-------------------
# S=Y | N | 0.368421052631579
# S=Y | Y | 0.631578947368421
# ---------+---+-------------------
# S=N | N | 0.790322580645161
# S=N | Y | 0.209677419354839
# ---------+---+-------------------
#
# category | F | P( F | category )
#
---------+------+-----------------------------------------------------------
# S=Y | real |
Gaussian(mean=1.36842105263158,stddev=0.935836242984963)
#
---------+------+-----------------------------------------------------------
# S=N | real |
Gaussian(mean=0.387096774193548,stddev=0.793363503758019)
#
---------+------+-----------------------------------------------------------
#
# '
# Failed test at t/7.t line 103.
# got: 'Model:
# category | P(category)
# ---------+----------------------
# Spam=Y | 0.46965699208443
# Spam=N | 0.53034300791556
# ---------+----------------------
#
# category | Caps | P( Caps | category )
# ---------+------+----------------------
# Spam=Y | N | 0.36516853932584
# Spam=Y | Y | 0.63483146067415
# ---------+------+----------------------
# Spam=N | N | 0.63681592039800
# Spam=N | Y | 0.36318407960199
# ---------+------+----------------------
#
# category | Free | P( Free | category )
# ---------+------+----------------------
# Spam=Y | N | 0.35955056179775
# Spam=Y | Y | 0.64044943820224
# ---------+------+----------------------
# Spam=N | N | 0.64676616915422
# Spam=N | Y | 0.35323383084577
# ---------+------+----------------------
#
# category | Html | P( Html | category )
# ---------+------+----------------------
# Spam=Y | N | 0.37640449438202
# Spam=Y | Y | 0.62359550561797
# ---------+------+----------------------
# Spam=N | N | 0.66666666666666
# Spam=N | Y | 0.33333333333333
# ---------+------+----------------------
#
# '
# expected: 'Model:
# category | P(category)
# ---------+-------------------
# Spam=Y | 0.46965699208443
# Spam=N | 0.53034300791556
# ---------+-------------------
#
# category | Caps | P( Caps | category )
# ---------+------+----------------------
# Spam=Y | N | 0.36516853932584
# Spam=Y | Y | 0.63483146067415
# ---------+------+----------------------
# Spam=N | N | 0.63681592039801
# Spam=N | Y | 0.36318407960199
# ---------+------+----------------------
#
# category | Free | P( Free | category )
# ---------+------+----------------------
# Spam=Y | N | 0.35955056179775
# Spam=Y | Y | 0.64044943820224
# ---------+------+----------------------
# Spam=N | N | 0.64676616915422
# Spam=N | Y | 0.35323383084577
# ---------+------+----------------------
#
# category | Html | P( Html | category )
# ---------+------+----------------------
# Spam=Y | N | 0.37640449438202
# Spam=Y | Y | 0.62359550561797
# ---------+------+----------------------
# Spam=N | N | 0.66666666666666
# Spam=N | Y | 0.33333333333333
# ---------+------+----------------------
#
# '
# Looks like you failed 5 tests of 12.
Dubious, test returned 5 (wstat 1280, 0x500)
Failed 5/12 subtests
t/8......ok
Test Summary Re****t
-------------------
t/1.t (Wstat: 768 Tests: 4 Failed: 3)
Failed tests: 2-4
Non-zero exit status: 3
t/2.t (Wstat: 768 Tests: 6 Failed: 3)
Failed tests: 2-4
Non-zero exit status: 3
t/3.t (Wstat: 768 Tests: 6 Failed: 3)
Failed tests: 2-4
Non-zero exit status: 3
t/4.t (Wstat: 768 Tests: 6 Failed: 3)
Failed tests: 2-4
Non-zero exit status: 3
t/5.t (Wstat: 768 Tests: 6 Failed: 3)
Failed tests: 2-4
Non-zero exit status: 3
t/6.t (Wstat: 1024 Tests: 9 Failed: 4)
Failed tests: 2-3, 6-7
Non-zero exit status: 4
t/7.t (Wstat: 1280 Tests: 12 Failed: 5)
Failed tests: 2-3, 6-7, 10
Non-zero exit status: 5
Files=8, Tests=51, 5 wallclock secs ( 0.02 usr 0.06 sys + 2.10 cusr
2.18 csys = 4.36 CPU)
Result: FAIL
Failed 7/8 test programs. 24/51 subtests failed.
make: *** [test_dynamic] Error 255
[MSG] [Sat Feb 2 02:17:18 2008] DEFAULT 'proceed_on_test_failure' HANDLER
RETURNING 'sub return value'
PREREQUISITES:
Here is a list of prerequisites you specified and versions we
managed to load:
Module Name Have Want
YAML 0.66 0.0
******************************** NOTE ********************************
The comments above are created mechanically, possibly without manual
checking by the sender. As there are many people performing automatic
tests on each upload to CPAN, it is likely that you will receive
identical messages about the same problem.
If you believe that the message is mistaken, please reply to the first
one with correction and/or additional informations, and do not take
it personally. We appreciate your patience. :)
**********************************************************************
Additional comments:
This re****t was machine-generated by CPAN::YACSmoke 0.03.
--
Summary of my perl5 (revision 5 version 8 subversion 8) configuration:
Platform:
osname=linux, osvers=2.6.22.10, archname=x86_64-linux-thread-multi-ld
uname='linux rinse 2.6.22.10 #1 smp sun oct 28 13:30:11 cst 2007
x86_64 gnulinux '
config_args='-d -Dusethreads -Dcc=gcc -Duselongdouble -Doptimize=-g
-O3 -Duse64bitint -Duse64bitall -Dprefix=/opt/perl/testers -Dd_dosuid
-Dinc_version_list=none -Acccdlflags=-fPIC -Duseshrplib=true
-Dcf_email=imacat@[EMAIL PROTECTED]
'
hint=recommended, useposix=true, d_sigaction=define
usethreads=define use5005threads=undef useithreads=define
usemultiplicity=define
useperlio=define d_sfio=undef uselargefiles=define usesocks=undef
use64bitint=define use64bitall=define uselongdouble=define
usemymalloc=n, bincompat5005=undef
Compiler:
cc='gcc', ccflags ='-D_REENTRANT -D_GNU_SOURCE -DTHREADS_HAVE_PIDS
-DDEBUGGING -fno-strict-aliasing -pipe -Wdeclaration-after-statement
-I/usr/local/include -D_LARGEFILE_SOURCE -D_FILE_OFFSET_BITS=64',
optimize='-g -O3',
cppflags='-D_REENTRANT -D_GNU_SOURCE -DTHREADS_HAVE_PIDS -DDEBUGGING
-fno-strict-aliasing -pipe -Wdeclaration-after-statement
-I/usr/local/include'
ccversion='', gccversion='4.1.2 20061115 (prerelease) (Debian
4.1.1-21)', gccosandvers=''
intsize=4, longsize=8, ptrsize=8, doublesize=8, byteorder=12345678
d_longlong=define, longlongsize=8, d_longdbl=define, longdblsize=16
ivtype='long', ivsize=8, nvtype='long double', nvsize=16,
Off_t='off_t', lseeksize=8
alignbytes=16, prototype=define
Linker and Libraries:
ld='gcc', ldflags =' -L/usr/local/lib'
libpth=/usr/local/lib /lib /usr/lib
libs=-lnsl -lgdbm -ldb -ldl -lm -lcrypt -lutil -lpthread -lc
perllibs=-lnsl -ldl -lm -lcrypt -lutil -lpthread -lc
libc=/lib/libc-2.3.6.so, so=so, useshrplib=true, libperl=libperl.so
gnulibc_version='2.3.6'
Dynamic Linking:
dlsrc=dl_dlopen.xs, dlext=so, d_dlsymun=undef, ccdlflags='-Wl,-E
-Wl,-rpath,/opt/perl/testers/lib/5.8.8/x86_64-linux-thread-multi-ld/CORE'
cccdlflags=' -fPIC', lddlflags='-shared -L/usr/local/lib'
|
