Data
primary-tumor

primary-tumor

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and all others as negative ('N'). Originally converted by Quan Sun.

18 features

binaryClass (target)nominal2 unique values
0 missing
agenominal3 unique values
0 missing
sexnominal2 unique values
1 missing
histologic-typenominal3 unique values
67 missing
degree-of-diffenominal3 unique values
155 missing
bonenominal2 unique values
0 missing
bone-marrownominal2 unique values
0 missing
lungnominal2 unique values
0 missing
pleuranominal2 unique values
0 missing
peritoneumnominal2 unique values
0 missing
livernominal2 unique values
0 missing
brainnominal2 unique values
0 missing
skinnominal2 unique values
1 missing
necknominal2 unique values
0 missing
supraclavicularnominal2 unique values
0 missing
axillarnominal2 unique values
1 missing
mediastinumnominal2 unique values
0 missing
abdominalnominal2 unique values
0 missing

62 properties

339
Number of instances (rows) of the dataset.
18
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
225
Number of missing values in the dataset.
207
Number of instances with at least one value missing.
0
Number of numeric attributes.
18
Number of nominal attributes.
83.33
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
1.23
Maximum entropy among attributes.
Minimum kurtosis among attributes of the numeric type.
61.06
Percentage of instances having missing values.
0.96
Third quartile of entropy among attributes.
Maximum kurtosis among attributes of the numeric type.
Minimum of means among attributes of the numeric type.
3.69
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.18
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
100
Percentage of nominal attributes.
0.03
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.
Minimum skewness among attributes of the numeric type.
0.51
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
Maximum skewness among attributes of the numeric type.
Minimum standard deviation of attributes of the numeric type.
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
Maximum standard deviation of attributes of the numeric type.
24.78
Percentage of instances belonging to the least frequent class.
First quartile of means among attributes of the numeric type.
0.38
Standard deviation of the number of distinct values among attributes of the nominal type.
0.76
Average entropy of the attributes.
84
Number of instances belonging to the least frequent class.
0
First quartile of mutual information between the nominal attributes and the target attribute.
Mean kurtosis among attributes of the numeric type.
15
Number of binary attributes.
First quartile of skewness among attributes of the numeric type.
Mean of means among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.61
Average class difference between consecutive instances.
0.04
Average mutual information between the nominal attributes and the target attribute.
0.84
Second quartile (Median) of entropy among attributes.
0.81
Entropy of the target attribute values.
20.26
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.05
Number of attributes divided by the number of instances.
2.17
Average number of distinct values among the attributes of the nominal type.
Second quartile (Median) of means among attributes of the numeric type.
22.56
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Mean skewness among attributes of the numeric type.
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
75.22
Percentage of instances belonging to the most frequent class.
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of skewness among attributes of the numeric type.
255
Number of instances belonging to the most frequent class.
0.15
Minimal entropy among attributes.

6 tasks

554 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
198 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
0 runs - estimation_procedure: 33% Holdout set - target_feature: binaryClass
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
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