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8218

Run 8218

Task 30 (Supervised Classification) page-blocks Uploaded 22-05-2014 by Felicia West
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Flow

weka.ZeroR(1)Weka implementation of ZeroR
weka.A1DE(2)_F1
weka.A1DE(2)_M1.0
weka.AdaBoostM1_DecisionStump(2)_I10
weka.AdaBoostM1_DecisionStump(2)_P100
weka.AdaBoostM1_DecisionStump(2)_S1
weka.AdaBoostM1_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.AdaBoostM1_IBk(2)_I20
weka.AdaBoostM1_IBk(2)_P100
weka.AdaBoostM1_IBk(2)_S1
weka.AdaBoostM1_IBk(2)_Wweka.classifiers.lazy.IBk
weka.Bagging_NaiveBayes(2)_I80
weka.Bagging_NaiveBayes(2)_P100
weka.Bagging_NaiveBayes(2)_S1
weka.Bagging_NaiveBayes(2)_Wweka.classifiers.bayes.NaiveBayes
weka.Bagging_NaiveBayes(2)_num-slots1
weka.Bagging_OneR(2)_I160
weka.Bagging_OneR(2)_P100
weka.Bagging_OneR(2)_S1
weka.Bagging_OneR(2)_Wweka.classifiers.rules.OneR
weka.Bagging_OneR(2)_num-slots1
weka.BayesianLogisticRegression(2)_Dtrue
weka.BayesianLogisticRegression(2)_F2
weka.BayesianLogisticRegression(2)_H1
weka.BayesianLogisticRegression(2)_I100
weka.BayesianLogisticRegression(2)_Ntrue
weka.BayesianLogisticRegression(2)_P1
weka.BayesianLogisticRegression(2)_RR:0.01-316,3.16
weka.BayesianLogisticRegression(2)_S0.5
weka.BayesianLogisticRegression(2)_Tl5.0E-4
weka.BayesianLogisticRegression(2)_V0.27
weka.BayesianLogisticRegression(2)_seed1
weka.ComplementNaiveBayes(2)_S1.0
weka.GaussianProcesses_PolyKernel(3)_L1.0
weka.GaussianProcesses_PolyKernel(3)_N0
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0
weka.OneR(3)_B6
weka.PolyKernel(4)_C250007
weka.PolyKernel(4)_E1.0
weka.GaussianProcesses_NormalizedPolyKernel(2)_L1.0
weka.GaussianProcesses_NormalizedPolyKernel(2)_N0
weka.GaussianProcesses_NormalizedPolyKernel(2)_Kweka.classifiers.functions.supportVector.NormalizedPolyKernel
weka.NormalizedPolyKernel(2)_E2.0
weka.NormalizedPolyKernel(2)_C250007
weka.CVParameterSelection_ZeroR(2)_X10
weka.CVParameterSelection_ZeroR(2)_S1
weka.CVParameterSelection_ZeroR(2)_Wweka.classifiers.rules.ZeroR
weka.J48(13)_C0.25
weka.J48(13)_M2
weka.J48(28)_C0.25
weka.J48(28)_M2
weka.REPTree(9)_M2
weka.REPTree(9)_V0.001
weka.REPTree(9)_N3
weka.REPTree(9)_S1
weka.REPTree(9)_L-1
weka.REPTree(9)_I0.0
weka.RandomTree(10)_K0
weka.RandomTree(10)_M1.0
weka.RandomTree(10)_V0.001
weka.RandomTree(10)_S1
weka.RandomForest(5)_I100
weka.RandomForest(5)_K0
weka.RandomForest(5)_S1
weka.RandomForest(5)_num-slots1
weka.MultilayerPerceptronCS(1)_Ha
weka.A1DE(4)_F1
weka.A1DE(4)_M1.0
weka.BayesNet_K2(6)_Dtrue
weka.BayesNet_K2(6)_Qweka.classifiers.bayes.net.search.local.K2
weka.K2(5)_P1
weka.K2(5)_SBAYES
weka.LibSVM(2)_S0
weka.LibSVM(2)_K2
weka.LibSVM(2)_D3
weka.LibSVM(2)_G0.0
weka.LibSVM(2)_R0.0
weka.LibSVM(2)_C1.0
weka.LibSVM(2)_N0.5
weka.LibSVM(2)_P0.1
weka.LibSVM(2)_M40.0
weka.LibSVM(2)_E0.001
weka.LibSVM(2)_model/Users/joa/Downloads/weka-3-7-12
weka.LibSVM(2)_seed1
weka.KernelLogisticRegression_RBFKernel(1)_S1
weka.KernelLogisticRegression_RBFKernel(1)_Kweka.classifiers.functions.supportVector.RBFKernel
weka.KernelLogisticRegression_RBFKernel(1)_L0.01
weka.KernelLogisticRegression_RBFKernel(1)_P1
weka.KernelLogisticRegression_RBFKernel(1)_E1
weka.RBFKernel(3)_G0.01
weka.RBFKernel(3)_C250007
weka.Bagging_REPTree(8)_P100
weka.Bagging_REPTree(8)_S1
weka.Bagging_REPTree(8)_num-slots1
weka.Bagging_REPTree(8)_I10
weka.Bagging_REPTree(8)_Wweka.classifiers.trees.REPTree
weka.ADTree(4)_B10
weka.ADTree(4)_E-3
weka.ADTree(4)_S1
weka.LADTree(4)_B10
weka.FilteredClassifier_Discretize_J48(4)_Fweka.filters.supervised.attribute.Discretize
weka.FilteredClassifier_Discretize_J48(4)_Wweka.classifiers.trees.J48
weka.Discretize(3)_Rfirst-last
weka.Discretize(3)_precision6
weka.RandomForest(8)_K0
weka.RandomForest(8)_S1
weka.RandomForest(8)_num-slots1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.4992
Per class
F measure
0.8493
Per class
KB relative information score
-6.0138
Mean absolute error
0.0762
Mean prior absolute error
0.0762
Number of instances
5473
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8058
Per class
Predictive accuracy
0.8977
Prior entropy
0.6391
Recall
0.8977
Per class
Relative absolute error
1.0003
Root mean prior squared error
0.1949
Root mean squared error
0.1949
Root relative squared error
1
SciMark benchmark
928.2355[550.2336271358062936.3240650382722482.7975877024999911.80521739130441760.0170946291457]