Data
hill-valley

hill-valley

active ARFF Publicly available Visibility: public Uploaded 22-05-2015 by Rafael G. Mantovani
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Author: Lee Graham, Franz Oppacher Source: [UCI](http://archive.ics.uci.edu/ml/datasets/hill-valley) Please cite: Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y coordinate, the points will create either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain). See the original source for some examples of these graphs. In the original form, there are six files. This is the non-noisy version, with training and test sets merged. ### Attribute Information: 1-100: Labeled “X##”. Floating point values (numeric), the Y-values of the graphs. 101: Labeled “class”. Binary {0, 1} representing {valley, hill}

101 features

Class (target)nominal2 unique values
0 missing
V1numeric1170 unique values
0 missing
V2numeric1170 unique values
0 missing
V3numeric1175 unique values
0 missing
V4numeric1167 unique values
0 missing
V5numeric1174 unique values
0 missing
V6numeric1171 unique values
0 missing
V7numeric1169 unique values
0 missing
V8numeric1167 unique values
0 missing
V9numeric1172 unique values
0 missing
V10numeric1163 unique values
0 missing
V11numeric1173 unique values
0 missing
V12numeric1176 unique values
0 missing
V13numeric1168 unique values
0 missing
V14numeric1166 unique values
0 missing
V15numeric1166 unique values
0 missing
V16numeric1179 unique values
0 missing
V17numeric1166 unique values
0 missing
V18numeric1171 unique values
0 missing
V19numeric1164 unique values
0 missing
V20numeric1171 unique values
0 missing
V21numeric1170 unique values
0 missing
V22numeric1164 unique values
0 missing
V23numeric1172 unique values
0 missing
V24numeric1170 unique values
0 missing
V25numeric1172 unique values
0 missing
V26numeric1163 unique values
0 missing
V27numeric1166 unique values
0 missing
V28numeric1170 unique values
0 missing
V29numeric1166 unique values
0 missing
V30numeric1168 unique values
0 missing
V31numeric1174 unique values
0 missing
V32numeric1166 unique values
0 missing
V33numeric1168 unique values
0 missing
V34numeric1167 unique values
0 missing
V35numeric1177 unique values
0 missing
V36numeric1164 unique values
0 missing
V37numeric1167 unique values
0 missing
V38numeric1164 unique values
0 missing
V39numeric1160 unique values
0 missing
V40numeric1168 unique values
0 missing
V41numeric1163 unique values
0 missing
V42numeric1168 unique values
0 missing
V43numeric1172 unique values
0 missing
V44numeric1168 unique values
0 missing
V45numeric1167 unique values
0 missing
V46numeric1157 unique values
0 missing
V47numeric1173 unique values
0 missing
V48numeric1170 unique values
0 missing
V49numeric1157 unique values
0 missing
V50numeric1167 unique values
0 missing
V51numeric1178 unique values
0 missing
V52numeric1167 unique values
0 missing
V53numeric1171 unique values
0 missing
V54numeric1179 unique values
0 missing
V55numeric1166 unique values
0 missing
V56numeric1174 unique values
0 missing
V57numeric1179 unique values
0 missing
V58numeric1170 unique values
0 missing
V59numeric1169 unique values
0 missing
V60numeric1166 unique values
0 missing
V61numeric1172 unique values
0 missing
V62numeric1167 unique values
0 missing
V63numeric1169 unique values
0 missing
V64numeric1167 unique values
0 missing
V65numeric1168 unique values
0 missing
V66numeric1167 unique values
0 missing
V67numeric1168 unique values
0 missing
V68numeric1160 unique values
0 missing
V69numeric1165 unique values
0 missing
V70numeric1170 unique values
0 missing
V71numeric1164 unique values
0 missing
V72numeric1175 unique values
0 missing
V73numeric1167 unique values
0 missing
V74numeric1176 unique values
0 missing
V75numeric1162 unique values
0 missing
V76numeric1167 unique values
0 missing
V77numeric1170 unique values
0 missing
V78numeric1152 unique values
0 missing
V79numeric1169 unique values
0 missing
V80numeric1166 unique values
0 missing
V81numeric1178 unique values
0 missing
V82numeric1173 unique values
0 missing
V83numeric1172 unique values
0 missing
V84numeric1165 unique values
0 missing
V85numeric1172 unique values
0 missing
V86numeric1167 unique values
0 missing
V87numeric1170 unique values
0 missing
V88numeric1167 unique values
0 missing
V89numeric1173 unique values
0 missing
V90numeric1165 unique values
0 missing
V91numeric1174 unique values
0 missing
V92numeric1173 unique values
0 missing
V93numeric1166 unique values
0 missing
V94numeric1160 unique values
0 missing
V95numeric1161 unique values
0 missing
V96numeric1166 unique values
0 missing
V97numeric1170 unique values
0 missing
V98numeric1179 unique values
0 missing
V99numeric1163 unique values
0 missing
V100numeric1175 unique values
0 missing

107 properties

1212
Number of instances (rows) of the dataset.
101
Number of attributes (columns) of the dataset.
2
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.
100
Number of numeric attributes.
1
Number of nominal attributes.
First quartile of entropy among attributes.
3.03
Third quartile of skewness among attributes of the numeric type.
0
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
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
9.59
Mean kurtosis among attributes of the numeric type.
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
9.22
First quartile of kurtosis among attributes of the numeric type.
18115.64
Third quartile of standard deviation of attributes of the numeric type.
0.5
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
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
8174.05
Mean of means among attributes of the numeric type.
0.49
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
8140.37
First quartile of means among attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.5
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
0.46
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.47
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
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
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.5
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.
1
Number of binary attributes.
2.97
First quartile of skewness among attributes of the numeric type.
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.5
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.
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
17868.73
First quartile of standard deviation of attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.5
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
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
3
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.47
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0
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
0.45
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
50
Percentage of instances belonging to the most frequent class.
18000.31
Mean standard deviation of attributes of the numeric type.
9.46
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1
Entropy of the target attribute values.
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
606
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
8169.53
Second quartile (Median) of means among attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
8.82
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.47
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.49
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
11.47
Maximum kurtosis among attributes of the numeric type.
8089.07
Minimum of means among attributes of the numeric type.
3
Second quartile (Median) of skewness among attributes of the numeric type.
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.01
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
8315.01
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
17981.7
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.08
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
0.99
Percentage of binary attributes.
Third quartile of entropy among attributes.
0.46
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.
2
The maximum number of distinct values among attributes of the nominal type.
2.92
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
9.91
Third quartile of kurtosis among attributes of the numeric type.
0.51
Average class difference between consecutive instances.
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.17
Maximum skewness among attributes of the numeric type.
17668.98
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
8198.98
Third quartile of means among attributes of the numeric type.
0.5
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
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
18604.51
Maximum standard deviation of attributes of the numeric type.
50
Percentage of instances belonging to the least frequent class.
99.01
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.5
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
0.46
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
606
Number of instances belonging to the least frequent class.
0.99
Percentage of nominal attributes.

15 tasks

92422 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
84656 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature:
0 runs - target_feature: Class
1309 runs - target_feature: Class
1308 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
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