Run 795

Task 94 (Learning Curve) dermatology Uploaded 08-04-2014 by Jan van Rijn
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weka.ZeroR(1)	Weka implementation of ZeroR
weka.A1DE(2)_F	1
weka.A1DE(2)_M	1.0
weka.AdaBoostM1_DecisionStump(2)_I	10
weka.AdaBoostM1_DecisionStump(2)_P	100
weka.AdaBoostM1_DecisionStump(2)_S	1
weka.AdaBoostM1_DecisionStump(2)_W	weka.classifiers.trees.DecisionStump
weka.AdaBoostM1_IBk(2)_I	20
weka.AdaBoostM1_IBk(2)_P	100
weka.AdaBoostM1_IBk(2)_S	1
weka.AdaBoostM1_IBk(2)_W	weka.classifiers.lazy.IBk
weka.Bagging_NaiveBayes(2)_I	80
weka.Bagging_NaiveBayes(2)_P	100
weka.Bagging_NaiveBayes(2)_S	1
weka.Bagging_NaiveBayes(2)_W	weka.classifiers.bayes.NaiveBayes
weka.Bagging_NaiveBayes(2)_num-slots	1
weka.Bagging_OneR(2)_I	160
weka.Bagging_OneR(2)_P	100
weka.Bagging_OneR(2)_S	1
weka.Bagging_OneR(2)_W	weka.classifiers.rules.OneR
weka.Bagging_OneR(2)_num-slots	1
weka.BayesianLogisticRegression(2)_D	true
weka.BayesianLogisticRegression(2)_F	2
weka.BayesianLogisticRegression(2)_H	1
weka.BayesianLogisticRegression(2)_I	100
weka.BayesianLogisticRegression(2)_N	true
weka.BayesianLogisticRegression(2)_P	1
weka.BayesianLogisticRegression(2)_R	R:0.01-316,3.16
weka.BayesianLogisticRegression(2)_S	0.5
weka.BayesianLogisticRegression(2)_Tl	5.0E-4
weka.BayesianLogisticRegression(2)_V	0.27
weka.BayesianLogisticRegression(2)_seed	1
weka.ComplementNaiveBayes(2)_S	1.0
weka.GaussianProcesses_PolyKernel(3)_L	1.0
weka.GaussianProcesses_PolyKernel(3)_N	0
weka.IBk(2)_A	true
weka.IBk(2)_K	1
weka.IBk(2)_W	0
weka.OneR(3)_B	6
weka.PolyKernel(4)_C	250007
weka.PolyKernel(4)_E	1.0
weka.GaussianProcesses_NormalizedPolyKernel(2)_L	1.0
weka.GaussianProcesses_NormalizedPolyKernel(2)_N	0
weka.GaussianProcesses_NormalizedPolyKernel(2)_K	weka.classifiers.functions.supportVector.NormalizedPolyKernel
weka.NormalizedPolyKernel(2)_E	2.0
weka.NormalizedPolyKernel(2)_C	250007
weka.CVParameterSelection_ZeroR(2)_X	10
weka.CVParameterSelection_ZeroR(2)_S	1
weka.CVParameterSelection_ZeroR(2)_W	weka.classifiers.rules.ZeroR
weka.J48(13)_C	0.25
weka.J48(13)_M	2
weka.J48(28)_C	0.25
weka.J48(28)_M	2
weka.REPTree(9)_M	2
weka.REPTree(9)_V	0.001
weka.REPTree(9)_N	3
weka.REPTree(9)_S	1
weka.REPTree(9)_L	-1
weka.REPTree(9)_I	0.0
weka.RandomTree(10)_K	0
weka.RandomTree(10)_M	1.0
weka.RandomTree(10)_V	0.001
weka.RandomTree(10)_S	1
weka.RandomForest(5)_I	100
weka.RandomForest(5)_K	0
weka.RandomForest(5)_S	1
weka.RandomForest(5)_num-slots	1
weka.MultilayerPerceptronCS(1)_H	a
weka.A1DE(4)_F	1
weka.A1DE(4)_M	1.0
weka.BayesNet_K2(6)_D	true
weka.BayesNet_K2(6)_Q	weka.classifiers.bayes.net.search.local.K2
weka.K2(5)_P	1
weka.K2(5)_S	BAYES
weka.LibSVM(2)_S	0
weka.LibSVM(2)_K	2
weka.LibSVM(2)_D	3
weka.LibSVM(2)_G	0.0
weka.LibSVM(2)_R	0.0
weka.LibSVM(2)_C	1.0
weka.LibSVM(2)_N	0.5
weka.LibSVM(2)_P	0.1
weka.LibSVM(2)_M	40.0
weka.LibSVM(2)_E	0.001
weka.LibSVM(2)_model	/Users/joa/Downloads/weka-3-7-12
weka.LibSVM(2)_seed	1
weka.KernelLogisticRegression_RBFKernel(1)_S	1
weka.KernelLogisticRegression_RBFKernel(1)_K	weka.classifiers.functions.supportVector.RBFKernel
weka.KernelLogisticRegression_RBFKernel(1)_L	0.01
weka.KernelLogisticRegression_RBFKernel(1)_P	1
weka.KernelLogisticRegression_RBFKernel(1)_E	1
weka.RBFKernel(3)_G	0.01
weka.RBFKernel(3)_C	250007
weka.Bagging_REPTree(8)_P	100
weka.Bagging_REPTree(8)_S	1
weka.Bagging_REPTree(8)_num-slots	1
weka.Bagging_REPTree(8)_I	10
weka.Bagging_REPTree(8)_W	weka.classifiers.trees.REPTree
weka.ADTree(4)_B	10
weka.ADTree(4)_E	-3
weka.ADTree(4)_S	1
weka.LADTree(4)_B	10
weka.FilteredClassifier_Discretize_J48(4)_F	weka.filters.supervised.attribute.Discretize
weka.FilteredClassifier_Discretize_J48(4)_W	weka.classifiers.trees.J48
weka.Discretize(3)_R	first-last
weka.Discretize(3)_precision	6
weka.RandomForest(8)_K	0
weka.RandomForest(8)_S	1
weka.RandomForest(8)_num-slots	1