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MLP_h-4
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=== Run information ===
Scheme: weka.classifiers.functions.MultilayerPerceptron -L 0.3 -M 0.2 -N 500 -V 0 -S 0 -E 20 -H 4 -G -R
Relation: Features_with_labels_All_windows.tsv.csv - Features_with_labels_All_windows.tsv.csv-weka.filters.unsupervised.attribute.Remove-R2-3
Instances: 530
Attributes: 16
Equpment
F1
F2
F3
F4
F5
F6
F7
F8
F9
F10
F11
F12
F13
F14
F15
Test mode: 10-fold cross-validation
=== Classifier model (full training set) ===
Sigmoid Node 0
Inputs Weights
Threshold -0.8746167848571353
Node 2 -10.986256931931011
Node 3 -14.317666146857032
Node 4 8.87795260456302
Node 5 10.36021461043818
Sigmoid Node 1
Inputs Weights
Threshold 0.8746155524426552
Node 2 10.98623406737459
Node 3 14.317639143484106
Node 4 -8.877935559144683
Node 5 -10.360194548324737
Sigmoid Node 2
Inputs Weights
Threshold 0.8413648144491421
Attrib F1 1.2044848831949382
Attrib F2 -1.9218926966884708
Attrib F3 -0.460456645646447
Attrib F4 -0.6520849345168668
Attrib F5 1.5826748829229733
Attrib F6 2.8224959066884687
Attrib F7 -2.8671014424452146
Attrib F8 7.4141941153914335
Attrib F9 4.874800038429693
Attrib F10 -6.783082719086083
Attrib F11 4.9406526892912375
Attrib F12 -4.210414850095258
Attrib F13 8.510566426377448
Attrib F14 4.033564340573637
Attrib F15 1.8408191023507288
Sigmoid Node 3
Inputs Weights
Threshold -0.13087612541028676
Attrib F1 2.5435137988854724
Attrib F2 2.7229547073083213
Attrib F3 3.6957811744782196
Attrib F4 2.815521064478484
Attrib F5 0.7734676290469289
Attrib F6 0.7023625805577374
Attrib F7 9.437830478334408
Attrib F8 7.313118373664815
Attrib F9 0.6078339562324243
Attrib F10 -8.655549842213702
Attrib F11 1.0662897136746519
Attrib F12 -4.069876931627321
Attrib F13 -3.122954451155163
Attrib F14 -6.084281556059733
Attrib F15 7.17247398135263
Sigmoid Node 4
Inputs Weights
Threshold -0.873350462225779
Attrib F1 -0.19212948834706947
Attrib F2 -8.806983370863797
Attrib F3 -1.1214068391093315
Attrib F4 -1.2418916615835194
Attrib F5 -0.21747044718722558
Attrib F6 5.7973196746815505
Attrib F7 -6.17342664019331
Attrib F8 -2.858400650346184
Attrib F9 -8.469457709369665
Attrib F10 8.835928042559228
Attrib F11 -1.4423840247544812
Attrib F12 17.194446888553497
Attrib F13 2.086177315868944
Attrib F14 -1.5060740533079613
Attrib F15 1.9660560314673374
Sigmoid Node 5
Inputs Weights
Threshold -3.744589830184962
Attrib F1 0.9334169210818476
Attrib F2 -0.35204490559444424
Attrib F3 -2.11626280487471
Attrib F4 -1.6625978035608917
Attrib F5 5.658814206493591
Attrib F6 4.799550348898993
Attrib F7 7.47811907730066
Attrib F8 3.7118433316639003
Attrib F9 -4.853340717190128
Attrib F10 6.658845370741623
Attrib F11 5.6152197322644515
Attrib F12 -8.789756578322825
Attrib F13 -8.957324941480625
Attrib F14 -5.247788016678408
Attrib F15 0.30752362472028466
Class n
Input
Node 0
Class o
Input
Node 1
Time taken to build model: 2.74 seconds
=== Stratified cross-validation ===
=== Summary ===
Correctly Classified Instances 479 90.3774 %
Incorrectly Classified Instances 51 9.6226 %
Kappa statistic 0.8075
Mean absolute error 0.1001
Root mean squared error 0.2812
Relative absolute error 20.0186 %
Root relative squared error 56.2359 %
Total Number of Instances 530
=== Detailed Accuracy By Class ===
TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class
0.901 0.094 0.905 0.901 0.903 0.808 0.956 0.958 n
0.906 0.099 0.903 0.906 0.905 0.808 0.956 0.927 o
Weighted Avg. 0.904 0.096 0.904 0.904 0.904 0.808 0.956 0.942
=== Confusion Matrix ===
a b <-- classified as
237 26 | a = n
25 242 | b = o