Data
Waveform-train

Waveform-train

in_preparation ARFF Publicly available Visibility: public Uploaded 20-06-2017 by Stefan Coors
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Source: Original Owners: Breiman,L., Friedman,J.H., Olshen,R.A., & Stone,C.J. (1984). Classification and Regression Trees. Wadsworth International Group: Belmont, California. (see pages 43-49). Donor: David Aha Data Set Information: Notes: -- 3 classes of waves -- 21 attributes, all of which include noise -- See the book for details (49-55, 169) -- waveform.data.Z contains 5000 instances Attribute Information: -- Each class is generated from a combination of 2 of 3 "base" waves -- Each instance is generated f added noise (mean 0, variance 1) in each attribute -- See the book for details (49-55, 169) #autoxgboost #autoweka

41 features

x1numeric501 unique values
0 missing
x2numeric516 unique values
0 missing
x3numeric572 unique values
0 missing
x4numeric650 unique values
0 missing
x5numeric724 unique values
0 missing
x6numeric779 unique values
0 missing
x7numeric828 unique values
0 missing
x8numeric757 unique values
0 missing
x9numeric730 unique values
0 missing
x10numeric676 unique values
0 missing
x11numeric709 unique values
0 missing
x12numeric679 unique values
0 missing
x13numeric725 unique values
0 missing
x14numeric761 unique values
0 missing
x15numeric844 unique values
0 missing
x16numeric760 unique values
0 missing
x17numeric711 unique values
0 missing
x18numeric648 unique values
0 missing
x19numeric566 unique values
0 missing
x20numeric526 unique values
0 missing
x21numeric492 unique values
0 missing
x22numeric494 unique values
0 missing
x23numeric488 unique values
0 missing
x24numeric495 unique values
0 missing
x25numeric495 unique values
0 missing
x26numeric490 unique values
0 missing
x27numeric494 unique values
0 missing
x28numeric505 unique values
0 missing
x29numeric492 unique values
0 missing
x30numeric490 unique values
0 missing
x31numeric505 unique values
0 missing
x32numeric496 unique values
0 missing
x33numeric504 unique values
0 missing
x34numeric503 unique values
0 missing
x35numeric505 unique values
0 missing
x36numeric486 unique values
0 missing
x37numeric488 unique values
0 missing
x38numeric490 unique values
0 missing
x39numeric492 unique values
0 missing
x40numeric506 unique values
0 missing
classnominal3 unique values
0 missing

62 properties

3500
Number of instances (rows) of the dataset.
41
Number of attributes (columns) of the dataset.
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.
40
Number of numeric attributes.
1
Number of nominal attributes.
-0.03
First quartile of skewness among attributes of the numeric type.
0.9
Mean of means among attributes of the numeric type.
1
First quartile of standard deviation of attributes of the numeric type.
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-0.08
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.01
Number of attributes divided by the number of instances.
3
Average number of distinct values among the attributes of the nominal type.
0.04
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.04
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
1.27
Mean standard deviation of attributes of the numeric type.
0.02
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
1.02
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.66
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.11
Maximum kurtosis among attributes of the numeric type.
-0.02
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
-0.01
Third quartile of kurtosis among attributes of the numeric type.
3.34
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
97.56
Percentage of numeric attributes.
1.99
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
3
The minimal number of distinct values among attributes of the nominal type.
2.44
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
3
The maximum number of distinct values among attributes of the nominal type.
-0.24
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
0.07
Third quartile of skewness among attributes of the numeric type.
0.28
Maximum skewness among attributes of the numeric type.
0.97
Minimum standard deviation of attributes of the numeric type.
-0.49
First quartile of kurtosis among attributes of the numeric type.
1.65
Third quartile of standard deviation of attributes of the numeric type.
2.01
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
-0.01
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
-0.2
Mean kurtosis among attributes of the numeric type.

16 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - 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
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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