Data
stress

stress

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#modelage

13 features

Surpoids (target)nominal2 unique values
3 missing
Sexenominal2 unique values
0 missing
Agenumeric60 unique values
0 missing
Poidsnumeric72 unique values
0 missing
Taillenumeric58 unique values
0 missing
Consommation_tabacnominal5 unique values
0 missing
type_consommationnominal2 unique values
168 missing
Allergiesnominal2 unique values
8 missing
stresse_a_cet_instantnumeric10 unique values
2 missing
nature_stresseenumeric10 unique values
2 missing
pression_au_travailnumeric10 unique values
6 missing
evenements_stressant_derniers_moisnumeric10 unique values
6 missing
Stress_dernier_moisnumeric10 unique values
7 missing

62 properties

202
Number of instances (rows) of the dataset.
13
Number of attributes (columns) of the dataset.
3
Number of distinct values of the target attribute (if it is nominal).
202
Number of missing values in the dataset.
172
Number of instances with at least one value missing.
8
Number of numeric attributes.
5
Number of nominal attributes.
0.72
Entropy of the target attribute values.
22.39
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0.9
Second quartile (Median) of entropy among attributes.
0.06
Number of attributes divided by the number of instances.
2.6
Average number of distinct values among the attributes of the nominal type.
-0.4
Second quartile (Median) of kurtosis among attributes of the numeric type.
20.07
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.47
Mean skewness among attributes of the numeric type.
4.3
Second quartile (Median) of means among attributes of the numeric type.
78.71
Percentage of instances belonging to the most frequent class.
10.43
Mean standard deviation of attributes of the numeric type.
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
159
Number of instances belonging to the most frequent class.
0.54
Minimal entropy among attributes.
0.59
Second quartile (Median) of skewness among attributes of the numeric type.
1
Maximum entropy among attributes.
-0.77
Minimum kurtosis among attributes of the numeric type.
30.77
Percentage of binary attributes.
2.65
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.89
Maximum kurtosis among attributes of the numeric type.
3.68
Minimum of means among attributes of the numeric type.
85.15
Percentage of instances having missing values.
1
Third quartile of entropy among attributes.
150.25
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
7.69
Percentage of missing values.
0.11
Third quartile of kurtosis among attributes of the numeric type.
0.09
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
61.54
Percentage of numeric attributes.
43.82
Third quartile of means among attributes of the numeric type.
5
The maximum number of distinct values among attributes of the nominal type.
-0.91
Minimum skewness among attributes of the numeric type.
38.46
Percentage of nominal attributes.
0.08
Third quartile of mutual information between the nominal attributes and the target attribute.
1.06
Maximum skewness among attributes of the numeric type.
2.23
Minimum standard deviation of attributes of the numeric type.
0.61
First quartile of entropy among attributes.
0.75
Third quartile of skewness among attributes of the numeric type.
25.92
Maximum standard deviation of attributes of the numeric type.
1.49
Percentage of instances belonging to the least frequent class.
-0.67
First quartile of kurtosis among attributes of the numeric type.
23.59
Third quartile of standard deviation of attributes of the numeric type.
0.84
Average entropy of the attributes.
3
Number of instances belonging to the least frequent class.
3.84
First quartile of means among attributes of the numeric type.
1.34
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.26
Mean kurtosis among attributes of the numeric type.
4
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
30.6
Mean of means among attributes of the numeric type.
0.46
First quartile of skewness among attributes of the numeric type.
0.72
Average class difference between consecutive instances.
0.04
Average mutual information between the nominal attributes and the target attribute.
2.37
First quartile of standard deviation of attributes of the numeric type.

9 tasks

28 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Surpoids
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
0 runs - estimation_procedure: 50 times Clustering
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