DEVELOPMENT... OpenML
Run
187500

Run 187500

Task 3886 (Supervised Classification) soybean Uploaded 25-02-2015 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.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

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

22 Evaluation measures

Area under ROC curve
0.9763
Per class
F measure
0.9706
Per class
Kappa
0.8732
KB relative information score
546.3726
Mean absolute error
0.0396
Mean prior absolute error
0.2339
Number of instances
683
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9705
Per class
Predictive accuracy
0.9707
Prior entropy
0.573
Recall
0.9707
Per class
Relative absolute error
0.1694
Root mean prior squared error
0.3414
Root mean squared error
0.1586
Root relative squared error
0.4646
SciMark benchmark
921.4023
UserCPU time millis
2330
UserCPU time millis testing
10
UserCPU time millis training
2320