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in_preparation ARFF public Visibility: public Uploaded 06-04-2017 by Pieter Gijsbers
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test auto

26 features

class (target)nominal5 unique values
0 missing
normalized-lossesnumeric52 unique values
0 missing
makenumeric22 unique values
0 missing
fuel-typenominal2 unique values
0 missing
aspirationnominal2 unique values
0 missing
num-of-doorsnominal3 unique values
0 missing
body-stylenominal5 unique values
0 missing
drive-wheelsnominal3 unique values
0 missing
engine-locationnominal2 unique values
0 missing
wheel-basenumeric53 unique values
0 missing
lengthnumeric75 unique values
0 missing
widthnumeric44 unique values
0 missing
heightnumeric48 unique values
0 missing
curb-weightnumeric168 unique values
0 missing
engine-typenominal7 unique values
0 missing
num-of-cylindersnominal7 unique values
0 missing
engine-sizenumeric44 unique values
0 missing
fuel-systemnominal8 unique values
0 missing
borenumeric39 unique values
0 missing
strokenumeric37 unique values
0 missing
compression-rationumeric32 unique values
0 missing
horsepowernumeric60 unique values
0 missing
peak-rpmnumeric24 unique values
0 missing
city-mpgnumeric29 unique values
0 missing
highway-mpgnumeric30 unique values
0 missing
pricenumeric184 unique values
0 missing

62 properties

202
Number of instances (rows) of the dataset.
26
Number of attributes (columns) of the dataset.
5
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.
16
Number of numeric attributes.
10
Number of nominal attributes.
98.35
Third quartile of means among attributes of the numeric type.
0.44
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.
0.38
Third quartile of mutual information between the nominal attributes and the target attribute.
8
The maximum number of distinct values among attributes of the nominal type.
-0.33
Minimum skewness among attributes of the numeric type.
38.46
Percentage of nominal attributes.
0.87
Third quartile of skewness among attributes of the numeric type.
2.59
Maximum skewness among attributes of the numeric type.
2.16
Minimum standard deviation of attributes of the numeric type.
0.57
First quartile of entropy among attributes.
18.15
Third quartile of standard deviation of attributes of the numeric type.
522.09
Maximum standard deviation of attributes of the numeric type.
10.89
Percentage of instances belonging to the least frequent class.
-1.17
First quartile of kurtosis among attributes of the numeric type.
2.32
Standard deviation of the number of distinct values among attributes of the nominal type.
1.1
Average entropy of the attributes.
22
Number of instances belonging to the least frequent class.
18.49
First quartile of means among attributes of the numeric type.
0.34
Mean kurtosis among attributes of the numeric type.
3
Number of binary attributes.
0.05
First quartile of mutual information between the nominal attributes and the target attribute.
209.73
Mean of means among attributes of the numeric type.
-0.18
First quartile of skewness among attributes of the numeric type.
0.76
Average class difference between consecutive instances.
0.21
Average mutual information between the nominal attributes and the target attribute.
5.52
First quartile of standard deviation of attributes of the numeric type.
2.19
Entropy of the target attribute values.
4.21
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1.18
Second quartile (Median) of entropy among attributes.
0.13
Number of attributes divided by the number of instances.
4.4
Average number of distinct values among the attributes of the nominal type.
-0.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
10.37
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.48
Mean skewness among attributes of the numeric type.
31.41
Second quartile (Median) of means among attributes of the numeric type.
33.17
Percentage of instances belonging to the most frequent class.
45.34
Mean standard deviation of attributes of the numeric type.
0.17
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
67
Number of instances belonging to the most frequent class.
0.11
Minimal entropy among attributes.
0.19
Second quartile (Median) of skewness among attributes of the numeric type.
1.97
Maximum entropy among attributes.
-1.33
Minimum kurtosis among attributes of the numeric type.
11.54
Percentage of binary attributes.
7.93
Second quartile (Median) of standard deviation of attributes of the numeric type.
1.63
Third quartile of entropy among attributes.
5.23
Maximum kurtosis among attributes of the numeric type.
10.16
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
0.68
Third quartile of kurtosis among attributes of the numeric type.
2549.5
Maximum of means among attributes of the numeric type.
0.04
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - 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
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