pkgeval/by_hash/1c84fa8_vs_7d3dac4/logs/DecisionTree/1.6.0-DEV-0669b64613.log

Julia Version 1.6.0-DEV.1153
Commit 0669b64613 (2020-10-07 09:01 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: AMD EPYC 7502 32-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-10.0.1 (ORCJIT, znver2)
Environment:
  JULIA_DEPOT_PATH = ::/usr/local/share/julia
  JULIA_NUM_THREADS = 2

  Resolving package versions...
  Installed ScikitLearnBase ─ v0.5.0
  Installed DecisionTree ──── v0.10.10
Updating `~/.julia/environments/v1.6/Project.toml`
  [7806a523] + DecisionTree v0.10.10
Updating `~/.julia/environments/v1.6/Manifest.toml`
  [7806a523] + DecisionTree v0.10.10
  [6e75b9c4] + ScikitLearnBase v0.5.0
  [2a0f44e3] + Base64
  [8bb1440f] + DelimitedFiles
  [8ba89e20] + Distributed
  [b77e0a4c] + InteractiveUtils
  [8f399da3] + Libdl
  [37e2e46d] + LinearAlgebra
  [56ddb016] + Logging
  [d6f4376e] + Markdown
  [a63ad114] + Mmap
  [9a3f8284] + Random
  [9e88b42a] + Serialization
  [6462fe0b] + Sockets
  [2f01184e] + SparseArrays
  [10745b16] + Statistics
  [8dfed614] + Test
    Testing DecisionTree
Status `/tmp/jl_sdeMQW/Project.toml`
  [7806a523] DecisionTree v0.10.10
  [6e75b9c4] ScikitLearnBase v0.5.0
  [8bb1440f] DelimitedFiles
  [8ba89e20] Distributed
  [37e2e46d] LinearAlgebra
  [9a3f8284] Random
  [10745b16] Statistics
  [8dfed614] Test
Status `/tmp/jl_sdeMQW/Manifest.toml`
  [7806a523] DecisionTree v0.10.10
  [6e75b9c4] ScikitLearnBase v0.5.0
  [2a0f44e3] Base64
  [8bb1440f] DelimitedFiles
  [8ba89e20] Distributed
  [b77e0a4c] InteractiveUtils
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [a63ad114] Mmap
  [9a3f8284] Random
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics
  [8dfed614] Test
    Testing Running tests...
Julia version: 1.6.0-DEV.1153
TEST: classification/random.jl 

Feature 2, Threshold 0.6056544585515548
L-> Feature 5, Threshold 0.3519102249662106
    L-> Feature 4, Threshold 0.3964305172913062
        L-> 1 : 61/97
        R-> 1 : 93/136
    R-> Feature 4, Threshold 0.5443369813935621
        L-> 0 : 116/195
        R-> 1 : 123/168
R-> Feature 3, Threshold 0.40770541203275457
    L-> Feature 5, Threshold 0.5034714805111138
        L-> 0 : 71/88
        R-> 0 : 50/82
    R-> Feature 1, Threshold 0.5347975865461467
        L-> 0 : 80/123
        R-> 1 : 77/111

##### nfoldCV Classification Tree #####

Mean Accuracy: 0.7027027027027026

Fold 1
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 3  16    0  0
 7  75   33  0
 0  26  153  2
 0   0   13  5
Accuracy: 0.7087087087087087
Kappa:    0.4713334097121067

Fold 2
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 13  12    0  0
 11  93   52  0
  0  17  115  3
  0   0   11  6
Accuracy: 0.6816816816816816
Kappa:    0.4737454155112263

Fold 3
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 6   12    0   0
 3  112   33   0
 0   27  111  10
 0    0    9  10
Accuracy: 0.7177177177177178
Kappa:    0.5210465916915309

Mean Accuracy: 0.7027027027027026

Fold 1
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 14    7    0   0
  5  108   30   0
  0   19  117  11
  0    0   12  10
Accuracy: 0.7477477477477478
Kappa:    0.5855570207280756

Fold 2
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 8   10    1  0
 4  100   35  0
 0   25  129  3
 0    0   14  4
Accuracy: 0.7237237237237237
Kappa:    0.5188088020481568

Fold 3
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 8  14    0  0
 4  89   45  0
 0  28  129  2
 0   0   10  4
Accuracy: 0.6906906906906907
Kappa:    0.4573544069485974

Mean Accuracy: 0.7207207207207208

##### nfoldCV Classification Forest #####

Mean Accuracy: 0.7897897897897899

Fold 1
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 4   15    0  0
 1  101   13  0
 0   31  149  1
 0    0   13  5
Accuracy: 0.7777777777777778
Kappa:    0.6032267413776446

Fold 2
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 2   23    0  0
 0  130   26  0
 0   18  117  0
 0    0    8  9
Accuracy: 0.7747747747747747
Kappa:    0.6074656188605108

Fold 3
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 10    8    0  0
  1  127   20  0
  0   22  126  0
  0    0   10  9
Accuracy: 0.8168168168168168
Kappa:    0.6835784161006917

Mean Accuracy: 0.7897897897897899

Fold 1
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 11   10    0  0
  3  128   12  0
  0   27  119  1
  0    0   18  4
Accuracy: 0.7867867867867868
Kappa:    0.6361887762167818

Fold 2
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 5   14    0  0
 1  127   11  0
 0   27  129  1
 0    0   12  6
Accuracy: 0.8018018018018018
Kappa:    0.6535241908785648

Fold 3
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 6   16    0  0
 1  124   13  0
 0   20  139  0
 0    0   10  4
Accuracy: 0.8198198198198198
Kappa:    0.6820547095049408

Mean Accuracy: 0.8028028028028028

##### nfoldCV Adaboosted Stumps #####

Mean Accuracy: 0.7807807807807808

Fold 1
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 0   19    0  0
 0  103   12  0
 0   25  156  0
 0    0   18  0
Accuracy: 0.7777777777777778
Kappa:    0.5914652342584303

Fold 2
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 0   25    0  0
 0  138   18  0
 0   17  118  0
 0    0   17  0
Accuracy: 0.7687687687687688
Kappa:    0.587460179554011

Fold 3
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 0   18    0  0
 2  127   19  0
 0   10  138  0
 0    0   19  0
Accuracy: 0.7957957957957958
Kappa:    0.6339772084377273

Mean Accuracy: 0.7807807807807808

Fold 1
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 0   21    0  0
 0  131   12  0
 0   24  121  2
 0    0   22  0
Accuracy: 0.7567567567567568
Kappa:    0.5711219232970808

Fold 2
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 0   19    0  0
 0  130    9  0
 0   32  125  0
 0    0   18  0
Accuracy: 0.7657657657657657
Kappa:    0.5801571137620016

Fold 3
Classes:  [-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 0   22    0  0
 1  126   11  0
 1   11  147  0
 0    0   14  0
Accuracy: 0.8198198198198198
Kappa:    0.6754122329623913

Mean Accuracy: 0.7807807807807808
==================================================
TEST: classification/low_precision.jl 


##### nfoldCV Classification Tree #####

Fold 1
Classes:  Int32[-2, -1, 0, 1, 2]
Matrix:   5×5 Matrix{Int64}:
 0   0   0    0   0
 1  31   4    0   0
 0   9  93   14   0
 0   0  18  125   8
 0   0   0   10  20
Accuracy: 0.8078078078078078
Kappa:    0.7071320599148

Fold 2
Classes:  Int32[-1, 0, 1, 2, 3]
Matrix:   5×5 Matrix{Int64}:
 28   13    0   0  0
  5  110   16   0  0
  0   19  104   9  0
  0    0    6  22  1
  0    0    0   0  0
Accuracy: 0.7927927927927928
Kappa:    0.6869746468128006

Fold 3
Classes:  Int32[-2, -1, 0, 1, 2, 3]
Matrix:   6×6 Matrix{Int64}:
 0   1   0    0   0  0
 0  24   7    0   0  0
 0  15  97   20   0  0
 0   0  13  114  12  0
 0   0   0   12  17  0
 0   0   0    0   1  0
Accuracy: 0.7567567567567568
Kappa:    0.6307142563765558

Mean Accuracy: 0.7857857857857858

##### nfoldCV Classification Forest #####

Fold 1
Classes:  Int32[-2, -1, 0, 1, 2]
Matrix:   5×5 Matrix{Int64}:
 0   1    0    0   0
 0  17   15    0   0
 0   0  111   12   0
 0   0   23  122   2
 0   0    0   12  18
Accuracy: 0.8048048048048048
Kappa:    0.6904496310279732

Fold 2
Classes:  Int32[-1, 0, 1, 2, 3]
Matrix:   5×5 Matrix{Int64}:
 14   25    0   0  0
  0  112    9   0  0
  0   12  131   1  0
  0    0    9  19  0
  0    0    0   1  0
Accuracy: 0.8288288288288288
Kappa:    0.7298847303258857

Fold 3
Classes:  Int32[-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 24   12    0   0
  0  120   16   0
  0   22  107   2
  0    0   14  16
Accuracy: 0.8018018018018018
Kappa:    0.6886704252486048

Mean Accuracy: 0.8118118118118117

##### nfoldCV Adaboosted Stumps #####

Fold 1
Classes:  Int32[-2, -1, 0, 1, 2]
Matrix:   5×5 Matrix{Int64}:
 0  0    1    0  0
 0  0   37    0  0
 0  0  107   25  0
 0  0   16  118  0
 0  0    0   29  0
Accuracy: 0.6756756756756757
Kappa:    0.4599107960774302

Fold 2
Classes:  Int32[-1, 0, 1, 2, 3]
Matrix:   5×5 Matrix{Int64}:
 0  34    0  0  0
 6  93   12  7  0
 3  23  112  5  0
 0   0   37  0  0
 0   0    1  0  0
Accuracy: 0.6156156156156156
Kappa:    0.38469533584513443

Fold 3
Classes:  Int32[-1, 0, 1, 2]
Matrix:   4×4 Matrix{Int64}:
 2   35    0  0
 0  105   25  0
 0   13  131  0
 0    0   22  0
Accuracy: 0.7147147147147147
Kappa:    0.5154917066147979

Mean Accuracy: 0.6686686686686687
==================================================
TEST: classification/heterogeneous.jl 

==================================================
TEST: classification/digits.jl 

==================================================
TEST: classification/iris.jl 

Feature 3, Threshold 2.45
L-> Iris-setosa : 50/50
R-> Feature 4, Threshold 1.75
    L-> Feature 3, Threshold 4.95
        L-> Feature 4, Threshold 1.65
            L-> Iris-versicolor : 47/47
            R-> Iris-virginica : 1/1
        R-> Feature 4, Threshold 1.55
            L-> Iris-virginica : 3/3
            R-> Feature 1, Threshold 6.95
                L-> Iris-versicolor : 2/2
                R-> Iris-virginica : 1/1
    R-> Feature 3, Threshold 4.85
        L-> Feature 2, Threshold 3.1
            L-> Iris-virginica : 2/2
            R-> Iris-versicolor : 1/1
        R-> Iris-virginica : 43/43

##### nfoldCV Classification Tree #####

Fold 1
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 21   0   0
  0  14   0
  0   2  13
Accuracy: 0.96
Kappa:    0.9390243902439024

Fold 2
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 17   0   0
  0  15   1
  0   0  17
Accuracy: 0.98
Kappa:    0.96996996996997

Fold 3
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 12   0   0
  0  18   2
  0   2  16
Accuracy: 0.92
Kappa:    0.8774509803921567

Mean Accuracy: 0.9533333333333333

##### nfoldCV Classification Forest #####

Fold 1
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 20   0   0
  0  16   2
  0   0  12
Accuracy: 0.96
Kappa:    0.9391727493917275

Fold 2
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 12   0   0
  0  12   1
  0   0  25
Accuracy: 0.98
Kappa:    0.9677419354838709

Fold 3
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 18   0   0
  0  18   1
  0   1  12
Accuracy: 0.96
Kappa:    0.9392466585662211

Mean Accuracy: 0.9666666666666667

##### nfoldCV Classification Adaboosted Stumps #####

Fold 1
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 18   0   0
  0  12   4
  0   1  15
Accuracy: 0.9
Kappa:    0.8497596153846155

Fold 2
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 13   0   0
  0  16   2
  0   1  18
Accuracy: 0.94
Kappa:    0.9088145896656534

Fold 3
Classes:  ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
Matrix:   3×3 Matrix{Int64}:
 19   0   0
  0  15   1
  0   3  12
Accuracy: 0.92
Kappa:    0.8792270531400966

Mean Accuracy: 0.9199999999999999
==================================================
TEST: classification/adult.jl 


##### 3 foldCV Classification Tree #####

Mean Accuracy: 0.8094228938235203

##### 3 foldCV Classification Forest #####

Mean Accuracy: 0.8408734912005897

##### nfoldCV Classification Adaboosted Stumps #####

Mean Accuracy: 0.8221996990079549
==================================================
TEST: classification/scikitlearn.jl 

==================================================
TEST: regression/random.jl 


##### nfoldCV Classification Tree #####

Mean Coeff of Determination: 0.5676904920580951

Fold 1
Mean Squared Error:     5.689407921915025
Correlation Coeff:      0.7395986162539963
Coeff of Determination: 0.5438771418946755

Fold 2
Mean Squared Error:     5.023869280682269
Correlation Coeff:      0.7677944154482331
Coeff of Determination: 0.5876646490326851

Fold 3
Mean Squared Error:     5.646374048377334
Correlation Coeff:      0.759919107345477
Coeff of Determination: 0.5715296852469246

Mean Coeff of Determination: 0.5676904920580951

Fold 1
Mean Squared Error:     5.528766733711038
Correlation Coeff:      0.7598540921993293
Coeff of Determination: 0.5716608471842237

Fold 2
Mean Squared Error:     4.952438218963306
Correlation Coeff:      0.7856766543569426
Coeff of Determination: 0.6144365226758415

Fold 3
Mean Squared Error:     5.191203956222338
Correlation Coeff:      0.7580046391579504
Coeff of Determination: 0.5678992566551814

Mean Coeff of Determination: 0.5846655421717489

##### nfoldCV Regression Forest #####

Mean Coeff of Determination: 0.8192789898535802

Fold 1
Mean Squared Error:     2.498334463649964
Correlation Coeff:      0.9166212070868418
Coeff of Determination: 0.7997071977079315

Fold 2
Mean Squared Error:     2.1293679097107834
Correlation Coeff:      0.930621610093323
Coeff of Determination: 0.825231586385963

Fold 3
Mean Squared Error:     2.2020646857659383
Correlation Coeff:      0.9316915538169335
Coeff of Determination: 0.8328981854668459

Mean Coeff of Determination: 0.8192789898535802

Fold 1
Mean Squared Error:     2.3231593118366995
Correlation Coeff:      0.9256085351943343
Coeff of Determination: 0.820014093663836

Fold 2
Mean Squared Error:     2.149812034538508
Correlation Coeff:      0.9346840694210115
Coeff of Determination: 0.8326301173316802

Fold 3
Mean Squared Error:     2.132086553949197
Correlation Coeff:      0.9263883281253541
Coeff of Determination: 0.8225313063007916

Mean Coeff of Determination: 0.8250585057654359
==================================================
TEST: regression/low_precision.jl 


##### nfoldCV Regression Tree #####

Fold 1
Mean Squared Error:     3.355703316064392
Correlation Coeff:      0.8663678103969371
Coeff of Determination: 0.7363436577666727

Fold 2
Mean Squared Error:     3.0957425850932085
Correlation Coeff:      0.8684074618564307
Coeff of Determination: 0.7468801179811493

Fold 3
Mean Squared Error:     3.0254345171080304
Correlation Coeff:      0.8786465388961409
Coeff of Determination: 0.7633923929053681

Mean Coeff of Determination: 0.74887205621773

##### nfoldCV Regression Forest #####

Fold 1
Mean Squared Error:     2.0134126115977136
Correlation Coeff:      0.9365495806493312
Coeff of Determination: 0.8349252243775604

Fold 2
Mean Squared Error:     2.5449452932505943
Correlation Coeff:      0.9207357540831301
Coeff of Determination: 0.8057017814523122

Fold 3
Mean Squared Error:     1.7914633978886536
Correlation Coeff:      0.9460405265149383
Coeff of Determination: 0.8563922362225096

Mean Coeff of Determination: 0.8323397473507942
==================================================
TEST: regression/digits.jl 


##### 3 foldCV Regression Tree #####

Mean Coeff of Determination: 0.7099156516877939

##### 3 foldCV Regression Forest #####

Mean Coeff of Determination: 0.6167291614726003
==================================================
TEST: regression/scikitlearn.jl 

==================================================
TEST: miscellaneous/convert.jl 

==================================================
Test Summary: | Pass  Total
Test Suites   |  144    144
    Testing DecisionTree tests passed 