Data
segment

segment

active ARFF Publicly available Visibility: public Uploaded 06-04-2014 by Jan van Rijn
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • study_14 study_1 study_1354 study_2120 study_2956 study_2958 study_2962 study_2964 study_2966 study_2968 study_2970 study_2971 study_2974 study_2975 study_2978 study_2979 study_2980 study_2984 study_2985 study_2988 study_2989 study_2992 study_2994 study_2996 study_2998 study_3000 study_3002 study_3003 study_5385 study_7949 study_8455 study_10634 study_2956 study_2958 study_2962 study_2964 study_2966 study_2968 study_2970 study_2971 study_2974 study_2975 study_2978 study_2979 study_2980 study_2984 study_2985 study_2988 study_2989 study_2992 study_2994 study_2996 study_2998 study_3000 study_3002 study_3003 study_531 study_567 study_2737 study_2956 study_2958 study_2962 study_2964 study_2966 study_2968 study_2970 study_2971 study_2974 study_2975 study_2978 study_2979 study_2980 study_2984 study_2985 study_2988 study_2989 study_2992 study_2994 study_2996 study_2998 study_3000 study_3002 study_3003 study_10244 study_10342 study_2598 study_2956 study_2958 study_2962 study_2964 study_2966 study_2968 study_2970 study_2971 study_2974 study_2975 study_2978 study_2979 study_2980 study_2984 study_2985 study_2988 study_2989 study_2992 study_2994 study_2996 study_2998 study_3000 study_3002 study_3003 study_3413 study_3962 study_5535 study_9155 study_2956 study_2958 study_2962 study_2964 study_2966 study_2968 study_2970 study_2971 study_2974 study_2975 study_2978 study_2979 study_2980 study_2984 study_2985 study_2988 study_2989 study_2992 study_2994 study_2996 study_2998 study_3000 study_3002 study_3003 study_4090 study_1684 study_2956 study_2958 study_2962 study_2964 study_2966 study_2968 study_2970 study_2971 study_2974 study_2975 study_2978 study_2979 study_2980 study_2984 study_2985 study_2988 study_2989 study_2992 study_2994 study_2996 study_2998 study_3000 study_3002 study_3003 study_3197 study_6381 study_10248 study_10255 study_7400 study_2921 study_3196 study_9244 study_4 study_1634 study_4196 study_6383 study_8579 study_1837 study_3293 study_4192 study_5865 study_7765 study_7949 study_10520 study_11132 study_11901 study_12920 study_10097 study_10432 study_533
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

20 features

class (target)nominal7 unique values
0 missing
region-centroid-colnumeric253 unique values
0 missing
region-centroid-rownumeric238 unique values
0 missing
region-pixel-countnumeric1 unique values
0 missing
short-line-density-5numeric4 unique values
0 missing
short-line-density-2numeric3 unique values
0 missing
vedge-meannumeric234 unique values
0 missing
vegde-sdnumeric1082 unique values
0 missing
hedge-meannumeric262 unique values
0 missing
hedge-sdnumeric1180 unique values
0 missing
intensity-meannumeric1271 unique values
0 missing
rawred-meannumeric681 unique values
0 missing
rawblue-meannumeric781 unique values
0 missing
rawgreen-meannumeric691 unique values
0 missing
exred-meannumeric430 unique values
0 missing
exblue-meannumeric636 unique values
0 missing
exgreen-meannumeric377 unique values
0 missing
value-meannumeric785 unique values
0 missing
saturation-meannumeric1899 unique values
0 missing
hue-meannumeric1922 unique values
0 missing

107 properties

2310
Number of instances (rows) of the dataset.
20
Number of attributes (columns) of the dataset.
7
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.
19
Number of numeric attributes.
1
Number of nominal attributes.
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.98
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
Standard deviation of the number of distinct values among attributes of the nominal type.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
7
Average number of distinct values among the attributes of the nominal type.
0.69
First quartile of skewness among attributes of the numeric type.
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.04
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.32
Mean skewness among attributes of the numeric type.
1.55
First quartile of standard deviation of attributes of the numeric type.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.95
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
0.05
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
14.29
Percentage of instances belonging to the most frequent class.
25.31
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.81
Entropy of the target attribute values.
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
330
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.69
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.22
Minimum kurtosis among attributes of the numeric type.
8.24
Second quartile (Median) of means among attributes of the numeric type.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.72
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
339.22
Maximum kurtosis among attributes of the numeric type.
-12.69
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
124.91
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
1.3
Second quartile (Median) of skewness among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
7
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
19.57
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.06
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.
7
The maximum number of distinct values among attributes of the nominal type.
-0.89
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
34.34
Third quartile of kurtosis among attributes of the numeric type.
0.15
Average class difference between consecutive instances.
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
16.9
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
37.05
Third quartile of means among attributes of the numeric type.
0.98
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
72.96
Maximum standard deviation of attributes of the numeric type.
14.29
Percentage of instances belonging to the least frequent class.
95
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.04
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
0.06
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
330
Number of instances belonging to the least frequent class.
5
Percentage of nominal attributes.
5.37
Third quartile of skewness among attributes of the numeric type.
0.95
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
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
38.52
Mean kurtosis among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
43.53
Third quartile of standard deviation of attributes of the numeric type.
0.98
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
24.63
Mean of means among attributes of the numeric type.
0.2
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.09
First quartile of kurtosis among attributes of the numeric type.
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.04
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
0.06
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.01
First quartile of means among attributes of the numeric type.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.95
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
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.98
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.

11 tasks

1 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10% Holdout set - target_feature: class
0 runs - estimation_procedure: Leave one out - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: class
0 runs - estimation_procedure: Test on Training Data - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Define a new task