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schizo

schizo

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Author: Source: Unknown - Date unknown Please cite: Schizophrenic Eye-Tracking Data in Rubin and Wu (1997) Biometrics. Yingnian Wu (wu@hustat.harvard.edu) [14/Oct/97] Information about the dataset CLASSTYPE: nominal CLASSINDEX: last

15 features

class (target)nominal2 unique values
0 missing
IDnumeric86 unique values
0 missing
targetnominal3 unique values
0 missing
gain_ratio_1numeric199 unique values
58 missing
gain_ratio_2numeric193 unique values
69 missing
gain_ratio_3numeric190 unique values
68 missing
gain_ratio_4numeric202 unique values
65 missing
gain_ratio_5numeric196 unique values
69 missing
gain_ratio_6numeric194 unique values
81 missing
gain_ratio_7numeric190 unique values
81 missing
gain_ratio_8numeric187 unique values
83 missing
gain_ratio_9numeric187 unique values
88 missing
gain_ratio_10numeric195 unique values
88 missing
gain_ratio_11numeric198 unique values
84 missing
sexnominal2 unique values
0 missing
Show all 15 features

107 properties

NumberOfInstances
340
Number of instances (rows) of the dataset.
NumberOfFeatures
15
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
834
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
228
Number of instances with at least one value missing.
NumberOfNumericFeatures
12
Number of numeric attributes.
NumberOfSymbolicFeatures
3
Number of nominal attributes.
AutoCorrelation
1
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.85
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
CfsSubsetEval_DecisionStumpErrRate
0.24
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
CfsSubsetEval_DecisionStumpKappa
0.51
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
CfsSubsetEval_NaiveBayesAUC
0.85
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
CfsSubsetEval_NaiveBayesErrRate
0.24
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
CfsSubsetEval_NaiveBayesKappa
0.51
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
CfsSubsetEval_kNN1NAUC
0.85
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
CfsSubsetEval_kNN1NErrRate
0.24
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
CfsSubsetEval_kNN1NKappa
0.51
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
ClassEntropy
1
Entropy of the target attribute values.
DecisionStumpAUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.04
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
66.81
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
52.06
Percentage of instances belonging to the most frequent class.
MajorityClassSize
177
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.39
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
2.71
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
134.68
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.03
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
3
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0.3
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
89.38
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.18
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
0.48
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
11.98
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.01
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
77.87
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2.33
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
-0.03
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
7.56
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.97
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.44
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.81
Minimum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.56
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.12
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
47.94
Percentage of instances belonging to the least frequent class.
MinorityClassSize
163
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.43
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.14
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
2
Number of binary attributes.
PercentageOfBinaryFeatures
13.33
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
67.06
Percentage of instances having missing values.
PercentageOfMissingValues
16.35
Percentage of missing values.
PercentageOfNumericFeatures
80
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
20
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.97
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.09
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.82
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.11
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.12
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.18
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.39
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.83
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-0.03
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.13
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
1.39
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.87
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
0.83
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.14
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.13
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0.58
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.43
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

24 tasks

Supervised Classification on schizo
505 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on schizo
212 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on schizo
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on schizo
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on schizo
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on schizo
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on schizo
0 runs
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
Clustering on schizo
0 runs - estimation_procedure: 50 times Clustering
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