Data
schizo

schizo

active ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
0 likes downloaded by 7 people , 7 total downloads 0 issues 0 downvotes
  • mythbusting_1 study_1 study_123 study_15 study_20 study_41 study_52
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
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

107 properties

340
Number of instances (rows) of the dataset.
15
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
834
Number of missing values in the dataset.
228
Number of instances with at least one value missing.
12
Number of numeric attributes.
3
Number of nominal attributes.
0.43
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.09
First quartile of kurtosis among attributes of the numeric type.
0.13
Third quartile of standard deviation of attributes of the numeric type.
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
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
11.98
Mean of means among attributes of the numeric type.
0.14
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.82
First quartile of means among attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.01
Average mutual information between the nominal attributes and the target attribute.
2
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
77.87
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-0.11
First quartile of skewness among attributes of the numeric type.
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.58
Standard deviation of the number of distinct values among attributes of the nominal type.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.33
Average number of distinct values among the attributes of the nominal type.
0.12
First quartile of standard deviation of attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.03
Mean skewness among attributes of the numeric type.
1.18
Second quartile (Median) of entropy among attributes.
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.43
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
52.06
Percentage of instances belonging to the most frequent class.
7.56
Mean standard deviation of attributes of the numeric type.
0.39
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1
Entropy of the target attribute values.
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
177
Number of instances belonging to the most frequent class.
0.97
Minimal entropy among attributes.
0.83
Second quartile (Median) of means among attributes of the numeric type.
0.83
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
1.39
Maximum entropy among attributes.
-1.44
Minimum kurtosis among attributes of the numeric type.
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.24
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.4
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
2.71
Maximum kurtosis among attributes of the numeric type.
0.81
Minimum of means among attributes of the numeric type.
-0.03
Second quartile (Median) of skewness among attributes of the numeric type.
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
134.68
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
13.33
Percentage of binary attributes.
0.13
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.04
Number of attributes divided by the number of instances.
0.03
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
67.06
Percentage of instances having missing values.
1.39
Third quartile of entropy among attributes.
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
66.81
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
3
The maximum number of distinct values among attributes of the nominal type.
-0.56
Minimum skewness among attributes of the numeric type.
16.35
Percentage of missing values.
0.87
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.3
Maximum skewness among attributes of the numeric type.
0.12
Minimum standard deviation of attributes of the numeric type.
80
Percentage of numeric attributes.
0.83
Third quartile of means among attributes of the numeric type.
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
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
89.38
Maximum standard deviation of attributes of the numeric type.
47.94
Percentage of instances belonging to the least frequent class.
20
Percentage of nominal attributes.
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.18
Average entropy of the attributes.
163
Number of instances belonging to the least frequent class.
0.97
First quartile of entropy among attributes.
0.14
Third quartile of skewness among attributes of the numeric type.
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
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.48
Mean kurtosis among attributes of the numeric type.
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

14 tasks

505 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
212 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
31 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
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task