Data
backache

backache

active ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
0 likes downloaded by 6 people , 6 total downloads 0 issues 0 downvotes
  • mythbusting_1 study_1 study_123 study_15 study_20 study_50 study_52 study_7 study_88
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: Source: Unknown - Date unknown Please cite: Data file: This data from "Problem-Solving" on "backache in pregnancy" is in somewhat different format from that listed in the book. Each integer is preceded by a space. This makes it easier to read. Each line is split in two separated by an ampersand. Each line also has a full stop (or period) at the end of each line which should be removed. If you have any queries, please contact me. Chris Chatfield. cc@maths.bath.ac.uk Information about the dataset CLASSTYPE: nominal CLASSINDEX: last

33 features

col_33 (target)nominal2 unique values
0 missing
id (row identifier)numeric180 unique values
0 missing
col_2nominal4 unique values
0 missing
col_3nominal10 unique values
0 missing
col_4numeric26 unique values
0 missing
col_5numeric12 unique values
0 missing
col_6numeric68 unique values
0 missing
col_7numeric77 unique values
0 missing
col_8numeric63 unique values
0 missing
col_9nominal8 unique values
0 missing
col_10nominal5 unique values
0 missing
col_11nominal2 unique values
0 missing
col_12nominal2 unique values
0 missing
col_13nominal2 unique values
0 missing
col_14nominal2 unique values
0 missing
col_15nominal2 unique values
0 missing
col_16nominal2 unique values
0 missing
col_17nominal2 unique values
0 missing
col_18nominal2 unique values
0 missing
col_19nominal2 unique values
0 missing
col_20nominal2 unique values
0 missing
col_21nominal2 unique values
0 missing
col_22nominal2 unique values
0 missing
col_23nominal2 unique values
0 missing
col_24nominal2 unique values
0 missing
col_25nominal2 unique values
0 missing
col_26nominal2 unique values
0 missing
col_27nominal2 unique values
0 missing
col_28nominal2 unique values
0 missing
col_29nominal2 unique values
0 missing
col_30nominal2 unique values
0 missing
col_31nominal2 unique values
0 missing
col_32nominal2 unique values
0 missing

107 properties

180
Number of instances (rows) of the dataset.
33
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.
6
Number of numeric attributes.
27
Number of nominal attributes.
43.28
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
23
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.18
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
-0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.7
Average number of distinct values among the attributes of the nominal type.
0.22
First quartile of skewness among attributes of the numeric type.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.49
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
1.96
Standard deviation of the number of distinct values among attributes of the nominal type.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.51
Mean skewness among attributes of the numeric type.
0.35
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.14
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
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.04
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.51
Mean standard deviation of attributes of the numeric type.
0.56
Second quartile (Median) of entropy among attributes.
0.18
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
0.19
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
86.11
Percentage of instances belonging to the most frequent class.
0.05
Minimal entropy among attributes.
0.44
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.58
Entropy of the target attribute values.
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
155
Number of instances belonging to the most frequent class.
-0.66
Minimum kurtosis among attributes of the numeric type.
26.02
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2.77
Maximum entropy among attributes.
1.61
Minimum of means among attributes of the numeric type.
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.18
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.14
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
4.62
Maximum kurtosis among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0.57
Second quartile (Median) of skewness among attributes of the numeric type.
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
70.68
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
69.7
Percentage of binary attributes.
5.56
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.42
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.18
Number of attributes divided by the number of instances.
0.06
Maximum mutual information between the nominal attributes and the target attribute.
0.17
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
0.77
Third quartile of entropy among attributes.
0.24
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
36.05
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.
0.07
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
2.65
Third quartile of kurtosis among attributes of the numeric type.
0.73
Average class difference between consecutive instances.
-0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.78
Maximum skewness among attributes of the numeric type.
13.89
Percentage of instances belonging to the least frequent class.
18.18
Percentage of numeric attributes.
65.16
Third quartile of means among attributes of the numeric type.
0.49
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
0.42
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11.17
Maximum standard deviation of attributes of the numeric type.
25
Number of instances belonging to the least frequent class.
81.82
Percentage of nominal attributes.
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
0.14
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
0.24
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.04
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.71
Average entropy of the attributes.
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.29
First quartile of entropy among attributes.
0.76
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
-0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.95
Mean kurtosis among attributes of the numeric type.
0.18
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.49
First quartile of kurtosis among attributes of the numeric type.
10.65
Third quartile of standard deviation of attributes of the numeric type.
0.49
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
0.42
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
32.23
Mean of means among attributes of the numeric type.
0.02
Average mutual information between the nominal attributes and the target attribute.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.41
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.14
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
0.24
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.04
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

6 tasks

174 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: col_33
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: col_33
0 runs - estimation_procedure: 33% Holdout set - target_feature: col_33
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: col_33
0 runs - estimation_procedure: 50 times Clustering
Define a new task