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InfoGainAttribute_RFk4_test.doc
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InfoGainAttribute_RFk4_test.doc
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=== Run information ===
Scheme: weka.classifiers.trees.RandomForest -P 100 -I 100 -num-slots 1 -K 4 -M 1.0 -V 0.001 -S 1
Relation: Allegheny_County_Crash_Data_Nominal-weka.filters.supervised.instance.Resample-B0.0-S1-Z33.0-no-replacement-V-weka.filters.unsupervised.attribute.Remove-R1-5,7-16,20-33,35-51,53-55,57-61,65-68
Instances: 8037
Attributes: 11
COLLISION_TYPE
PROPERTY_DAMAGE_ONLY
FATAL_OR_MAJ_INJ
INJURY
MOTORCYCLE
PEDESTRIAN
INJURY_OR_FATAL
MINOR_INJURY
MODERATE_INJURY
MAJOR_INJURY
MAX_SEVERITY_LEVEL
Test mode: evaluate on training data
=== Classifier model (full training set) ===
RandomForest
Bagging with 100 iterations and base learner
weka.classifiers.trees.RandomTree -K 4 -M 1.0 -V 0.001 -S 1 -do-not-check-capabilities
Time taken to build model: 0.38 seconds
=== Evaluation on training set ===
Time taken to test model on training data: 0.26 seconds
=== Summary ===
Correctly Classified Instances 7918 98.5193 %
Incorrectly Classified Instances 119 1.4807 %
Kappa statistic 0.9704
Mean absolute error 0.0203
Root mean squared error 0.1005
Relative absolute error 4.0649 %
Root relative squared error 20.1156 %
Total Number of Instances 8037
=== Detailed Accuracy By Class ===
TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class
0.972 0.000 1.000 0.972 0.986 0.971 0.999 0.999 NoInjury
1.000 0.028 0.970 1.000 0.985 0.971 0.999 0.999 Injury
Weighted Avg. 0.985 0.014 0.986 0.985 0.985 0.971 0.999 0.999
=== Confusion Matrix ===
a b <-- classified as
4074 118 | a = NoInjury
1 3844 | b = Injury
=== Re-evaluation on test set ===
User supplied test set
Relation: Allegheny_County_Crash_Data_Nominal-weka.filters.supervised.instance.Resample-B0.0-S1-Z33.0-no-replacement-weka.filters.unsupervised.attribute.Remove-R1-5,7-16,20-33,35-51,53-55,57-61,65-68
Instances: unknown (yet). Reading incrementally
Attributes: 11
=== Summary ===
Correctly Classified Instances 3909 98.787 %
Incorrectly Classified Instances 48 1.213 %
Kappa statistic 0.9757
Mean absolute error 0.0183
Root mean squared error 0.0942
Total Number of Instances 3957
=== Detailed Accuracy By Class ===
TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class
0.977 0.000 1.000 0.977 0.988 0.976 0.999 0.999 NoInjury
1.000 0.023 0.975 1.000 0.987 0.976 0.999 0.999 Injury
Weighted Avg. 0.988 0.011 0.988 0.988 0.988 0.976 0.999 0.999
=== Confusion Matrix ===
a b <-- classified as
2016 48 | a = NoInjury
0 1893 | b = Injury
=== Re-evaluation on test set ===
User supplied test set
Relation: Allegheny_County_Crash_Data_Nominal-weka.filters.supervised.instance.Resample-B0.0-S1-Z33.0-no-replacement-weka.filters.unsupervised.attribute.Remove-R1-5,7-16,20-33,35-51,53-55,57-61,65-68
Instances: unknown (yet). Reading incrementally
Attributes: 11
=== Summary ===
Correctly Classified Instances 3909 98.787 %
Incorrectly Classified Instances 48 1.213 %
Kappa statistic 0.9757
Mean absolute error 0.0183
Root mean squared error 0.0942
Total Number of Instances 3957
=== Detailed Accuracy By Class ===
TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class
0.977 0.000 1.000 0.977 0.988 0.976 0.999 0.999 NoInjury
1.000 0.023 0.975 1.000 0.987 0.976 0.999 0.999 Injury
Weighted Avg. 0.988 0.011 0.988 0.988 0.988 0.976 0.999 0.999
=== Confusion Matrix ===
a b <-- classified as
2016 48 | a = NoInjury
0 1893 | b = Injury
=== Re-evaluation on test set ===
User supplied test set
Relation: Allegheny_County_Crash_Data_Nominal-weka.filters.supervised.instance.Resample-B0.0-S1-Z33.0-no-replacement-weka.filters.unsupervised.attribute.Remove-R1-5,7-16,20-33,35-51,53-55,57-61,65-68
Instances: unknown (yet). Reading incrementally
Attributes: 11
=== Summary ===
Correctly Classified Instances 3909 98.787 %
Incorrectly Classified Instances 48 1.213 %
Kappa statistic 0.9757
Mean absolute error 0.0183
Root mean squared error 0.0942
Total Number of Instances 3957
=== Detailed Accuracy By Class ===
TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class
0.977 0.000 1.000 0.977 0.988 0.976 0.999 0.999 NoInjury
1.000 0.023 0.975 1.000 0.987 0.976 0.999 0.999 Injury
Weighted Avg. 0.988 0.011 0.988 0.988 0.988 0.976 0.999 0.999
=== Confusion Matrix ===
a b <-- classified as
2016 48 | a = NoInjury
0 1893 | b = Injury