Data
ML2017-challenge-2

ML2017-challenge-2

in_preparation ARFF Publicly available Visibility: public Uploaded 09-06-2017 by Jan van Rijn
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Machine Learning Summer Course Data Mining Challenge

12 features

A1 (target)nominal2 unique values
0 missing
A2numeric99 unique values
0 missing
A3numeric6941 unique values
0 missing
A4numeric19228 unique values
0 missing
A5numeric6064 unique values
0 missing
A6numeric3 unique values
0 missing
A7numeric3 unique values
0 missing
A8numeric30748 unique values
0 missing
A9numeric19803 unique values
0 missing
A10numeric25321 unique values
0 missing
A11numeric22381 unique values
0 missing
A12numeric30114 unique values
0 missing

62 properties

39948
Number of instances (rows) of the dataset.
12
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.
11
Number of numeric attributes.
1
Number of nominal attributes.
-0.24
First quartile of skewness among attributes of the numeric type.
8.7648640174263E+17
Mean of means among attributes of the numeric type.
65.87
First quartile of standard deviation of attributes of the numeric type.
0.72
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
0.65
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.
2.4
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
111150.9
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.
16.18
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
83.16
Percentage of instances belonging to the most frequent class.
4.5333677544489E+17
Mean standard deviation of attributes of the numeric type.
1.78
Second quartile (Median) of skewness among attributes of the numeric type.
33220
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
8.33
Percentage of binary attributes.
328374.22
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.12
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
27130.69
Maximum kurtosis among attributes of the numeric type.
1.46
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
32.13
Third quartile of kurtosis among attributes of the numeric type.
9.6413504191457E+18
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
91.67
Percentage of numeric attributes.
3669622.26
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
8.33
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-0.88
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
5.19
Third quartile of skewness among attributes of the numeric type.
159.06
Maximum skewness among attributes of the numeric type.
0.63
Minimum standard deviation of attributes of the numeric type.
-1.02
First quartile of kurtosis among attributes of the numeric type.
5841539.59
Third quartile of standard deviation of attributes of the numeric type.
4.9867045298743E+18
Maximum standard deviation of attributes of the numeric type.
16.84
Percentage of instances belonging to the least frequent class.
6728
Number of instances belonging to the least frequent class.
2.1
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.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
2475.84
Mean kurtosis among attributes of the numeric type.

10 tasks

59 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: A1
11 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: A1
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
Define a new task