Data
BNG(audiology,1000,10)

BNG(audiology,1000,10)

active ARFF public domain Visibility: public Uploaded 22-02-2015 by Jan van Rijn
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70 features

class (target)nominal24 unique values
0 missing
age_gt_60nominal2 unique values
0 missing
airnominal5 unique values
0 missing
airBoneGapnominal2 unique values
0 missing
ar_cnominal3 unique values
0 missing
ar_unominal3 unique values
0 missing
bonenominal4 unique values
0 missing
boneAbnormalnominal2 unique values
0 missing
bsernominal2 unique values
0 missing
history_buzzingnominal2 unique values
0 missing
history_dizzinessnominal2 unique values
0 missing
history_fluctuatingnominal2 unique values
0 missing
history_fullnessnominal2 unique values
0 missing
history_hereditynominal2 unique values
0 missing
history_nauseanominal2 unique values
0 missing
history_noisenominal2 unique values
0 missing
history_recruitmentnominal2 unique values
0 missing
history_ringingnominal2 unique values
0 missing
history_roaringnominal2 unique values
0 missing
history_vomitingnominal2 unique values
0 missing
late_wave_poornominal2 unique values
0 missing
m_at_2knominal2 unique values
0 missing
m_cond_lt_1knominal2 unique values
0 missing
m_gt_1knominal2 unique values
0 missing
m_m_gt_2knominal2 unique values
0 missing
m_m_snnominal2 unique values
0 missing
m_m_sn_gt_1knominal2 unique values
0 missing
m_m_sn_gt_2knominal2 unique values
0 missing
m_m_sn_gt_500nominal2 unique values
0 missing
m_p_sn_gt_2knominal2 unique values
0 missing
m_s_gt_500nominal2 unique values
0 missing
m_s_snnominal2 unique values
0 missing
m_s_sn_gt_1knominal2 unique values
0 missing
m_s_sn_gt_2knominal2 unique values
0 missing
m_s_sn_gt_3knominal2 unique values
0 missing
m_s_sn_gt_4knominal2 unique values
0 missing
m_sn_2_3knominal2 unique values
0 missing
m_sn_gt_1knominal2 unique values
0 missing
m_sn_gt_2knominal2 unique values
0 missing
m_sn_gt_3knominal2 unique values
0 missing
m_sn_gt_4knominal2 unique values
0 missing
m_sn_gt_500nominal2 unique values
0 missing
m_sn_gt_6knominal2 unique values
0 missing
m_sn_lt_1knominal2 unique values
0 missing
m_sn_lt_2knominal2 unique values
0 missing
m_sn_lt_3knominal2 unique values
0 missing
middle_wave_poornominal2 unique values
0 missing
mod_gt_4knominal2 unique values
0 missing
mod_mixednominal2 unique values
0 missing
mod_s_mixednominal2 unique values
0 missing
mod_s_sn_gt_500nominal2 unique values
0 missing
mod_snnominal2 unique values
0 missing
mod_sn_gt_1knominal2 unique values
0 missing
mod_sn_gt_2knominal2 unique values
0 missing
mod_sn_gt_3knominal2 unique values
0 missing
mod_sn_gt_4knominal2 unique values
0 missing
mod_sn_gt_500nominal2 unique values
0 missing
notch_4knominal2 unique values
0 missing
notch_at_4knominal2 unique values
0 missing
o_ar_cnominal3 unique values
0 missing
o_ar_unominal3 unique values
0 missing
s_sn_gt_1knominal2 unique values
0 missing
s_sn_gt_2knominal2 unique values
0 missing
s_sn_gt_4knominal2 unique values
0 missing
speechnominal6 unique values
0 missing
static_normalnominal2 unique values
0 missing
tympnominal5 unique values
0 missing
viith_nerve_signsnominal2 unique values
0 missing
wave_V_delayednominal2 unique values
0 missing
waveform_ItoV_prolongednominal2 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
70
Number of attributes (columns) of the dataset.
24
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
0
Number of numeric attributes.
70
Number of nominal attributes.
24
The maximum number of distinct values among attributes of the nominal type.
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
0.94
Third quartile of entropy among attributes.
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
211.75
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Maximum skewness among attributes of the numeric type.
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
0.13
Average class difference between consecutive instances.
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum standard deviation of attributes of the numeric type.
0.61
Percentage of instances belonging to the least frequent class.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.56
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.82
Average entropy of the attributes.
6126
Number of instances belonging to the least frequent class.
100
Percentage of nominal attributes.
0.02
Third quartile of mutual information between the nominal attributes and the target attribute.
0.57
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Mean kurtosis among attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.56
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean of means among attributes of the numeric type.
0.53
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.56
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.02
Average mutual information between the nominal attributes and the target attribute.
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of means among attributes of the numeric type.
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.57
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
48.25
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
61
Number of binary attributes.
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
0.58
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.54
Average number of distinct values among the attributes of the nominal type.
First quartile of skewness among attributes of the numeric type.
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
2.71
Standard deviation of the number of distinct values among attributes of the nominal type.
0.56
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean skewness among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.57
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean standard deviation of attributes of the numeric type.
0.6
Second quartile (Median) of entropy among attributes.
0.58
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.55
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
24.14
Percentage of instances belonging to the most frequent class.
0.49
Minimal entropy among attributes.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.53
Entropy of the target attribute values.
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
241431
Number of instances belonging to the most frequent class.
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of means among attributes of the numeric type.
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2.58
Maximum entropy among attributes.
Minimum of means among attributes of the numeric type.
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.58
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.7
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum kurtosis among attributes of the numeric type.
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of skewness among attributes of the numeric type.
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.1
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
87.14
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.

12 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
28 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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