Data
gina_prior2

gina_prior2

active ARFF Publicly available Visibility: public Uploaded 06-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Note: Identical to the MNIST dataset? Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF format) GINA is digit recognition database The task of GINA is handwritten digit recognition. Data type: non-sparse Number of features: 784 Number of examples and check-sum: Tot_ex Check_sum 3468 90979365.00

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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
pixel253numeric1 unique values
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0 missing
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0 missing
pixel254numeric6 unique values
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107 properties

3468
Number of instances (rows) of the dataset.
785
Number of attributes (columns) of the dataset.
10
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.
784
Number of numeric attributes.
1
Number of nominal attributes.
0.79
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
3468
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
137.57
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
3.18
Second quartile (Median) of skewness among attributes of the numeric type.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.23
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
10
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
36.7
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.39
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
-0.2
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
58.89
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
182.83
Third quartile of kurtosis among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.28
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
113.78
Maximum standard deviation of attributes of the numeric type.
9.08
Percentage of instances belonging to the least frequent class.
99.87
Percentage of numeric attributes.
68.91
Third quartile of means among attributes of the numeric type.
0.86
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
0.39
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
315
Number of instances belonging to the least frequent class.
0.13
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.29
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
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
410.26
Mean kurtosis among attributes of the numeric type.
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
13.09
Third quartile of skewness among attributes of the numeric type.
0.68
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
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.28
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
33.46
Mean of means among attributes of the numeric type.
0.29
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.19
First quartile of kurtosis among attributes of the numeric type.
101.19
Third quartile of standard deviation of attributes of the numeric type.
0.86
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
0.39
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.1
First quartile of means among attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.29
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
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.68
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
Standard deviation of the number of distinct values among attributes of the nominal type.
0.28
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
10
Average number of distinct values among the attributes of the nominal type.
0.78
First quartile of skewness among attributes of the numeric type.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.86
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
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
11.14
Mean skewness among attributes of the numeric type.
3.78
First quartile of standard deviation of attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.29
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
0.09
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
11.04
Percentage of instances belonging to the most frequent class.
49.11
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.68
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
3.32
Entropy of the target attribute values.
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
383
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
8.84
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.83
Minimum kurtosis among attributes of the numeric type.
6.97
Second quartile (Median) of means among attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

7 tasks

286 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: label
110 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: label
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: label
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: label
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task