Data
CF-metadataset

CF-metadataset

in_preparation ARFF Public Domain (CC0) Visibility: public Uploaded 03-04-2018 by Tiago Cunha
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Metadata regarding several Collaborative Filtering datasets associated with the best algorithms from MyMediaLite.

82 features

datasetnominal32 unique values
0 missing
colCounts_entropynumeric32 unique values
0 missing
colCounts_gininumeric32 unique values
0 missing
colCounts_kurtosisnumeric32 unique values
0 missing
colCounts_maxnumeric32 unique values
0 missing
colCounts_meannumeric32 unique values
0 missing
colCounts_mediannumeric13 unique values
0 missing
colCounts_minnumeric3 unique values
0 missing
colCounts_modenumeric5 unique values
0 missing
colCounts_sdnumeric32 unique values
0 missing
colCounts_skewnessnumeric32 unique values
0 missing
colMeans_entropynumeric32 unique values
0 missing
colMeans_gininumeric32 unique values
0 missing
colMeans_kurtosisnumeric32 unique values
0 missing
colMeans_maxnumeric13 unique values
0 missing
colMeans_meannumeric32 unique values
0 missing
colMeans_mediannumeric24 unique values
0 missing
colMeans_minnumeric4 unique values
0 missing
colMeans_modenumeric6 unique values
0 missing
colMeans_sdnumeric32 unique values
0 missing
colMeans_skewnessnumeric32 unique values
0 missing
colSums_entropynumeric32 unique values
0 missing
colSums_gininumeric32 unique values
0 missing
colSums_kurtosisnumeric32 unique values
0 missing
colSums_maxnumeric32 unique values
0 missing
colSums_meannumeric32 unique values
0 missing
colSums_mediannumeric19 unique values
0 missing
colSums_minnumeric4 unique values
0 missing
colSums_modenumeric8 unique values
0 missing
colSums_sdnumeric32 unique values
0 missing
colSums_skewnessnumeric32 unique values
0 missing
nitemsnumeric30 unique values
0 missing
nratingsnumeric32 unique values
0 missing
nusersnumeric32 unique values
0 missing
ratings_entropynumeric32 unique values
0 missing
ratings_gininumeric32 unique values
0 missing
ratings_kurtosisnumeric32 unique values
0 missing
ratings_maxnumeric1 unique values
0 missing
ratings_meannumeric32 unique values
0 missing
ratings_mediannumeric3 unique values
0 missing
ratings_minnumeric1 unique values
0 missing
ratings_modenumeric2 unique values
0 missing
ratings_sdnumeric32 unique values
0 missing
ratings_skewnessnumeric32 unique values
0 missing
rowCounts_entropynumeric32 unique values
0 missing
rowCounts_gininumeric32 unique values
0 missing
rowCounts_kurtosisnumeric32 unique values
0 missing
rowCounts_maxnumeric30 unique values
0 missing
rowCounts_meannumeric32 unique values
0 missing
rowCounts_mediannumeric10 unique values
0 missing
rowCounts_minnumeric4 unique values
0 missing
rowCounts_modenumeric6 unique values
0 missing
rowCounts_sdnumeric32 unique values
0 missing
rowCounts_skewnessnumeric32 unique values
0 missing
rowMeans_entropynumeric32 unique values
0 missing
rowMeans_gininumeric32 unique values
0 missing
rowMeans_kurtosisnumeric32 unique values
0 missing
rowMeans_maxnumeric16 unique values
0 missing
rowMeans_meannumeric32 unique values
0 missing
rowMeans_mediannumeric15 unique values
0 missing
rowMeans_minnumeric3 unique values
0 missing
rowMeans_modenumeric3 unique values
0 missing
rowMeans_sdnumeric32 unique values
0 missing
rowMeans_skewnessnumeric32 unique values
0 missing
rowSums_entropynumeric32 unique values
0 missing
rowSums_gininumeric32 unique values
0 missing
rowSums_kurtosisnumeric32 unique values
0 missing
rowSums_maxnumeric30 unique values
0 missing
rowSums_meannumeric32 unique values
0 missing
rowSums_mediannumeric12 unique values
0 missing
rowSums_minnumeric6 unique values
0 missing
rowSums_modenumeric9 unique values
0 missing
rowSums_sdnumeric32 unique values
0 missing
rowSums_skewnessnumeric32 unique values
0 missing
sparsitynumeric32 unique values
0 missing
target_nmaenominal8 unique values
0 missing
target_maenominal7 unique values
0 missing
target_rmsenominal7 unique values
0 missing
target_aucnominal3 unique values
0 missing
target_mapnominal5 unique values
0 missing
target_mrrnominal5 unique values
0 missing
target_ndcgnominal5 unique values
0 missing

62 properties

32
Number of instances (rows) of the dataset.
82
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.
74
Number of numeric attributes.
8
Number of nominal attributes.
55582.36
Mean of means among attributes of the numeric type.
-0.02
First quartile of skewness among attributes of the numeric type.
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.34
First quartile of standard deviation of attributes of the numeric type.
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.
Second quartile (Median) of entropy among attributes.
2.56
Number of attributes divided by the number of instances.
9
Average number of distinct values among the attributes of the nominal type.
4.85
Second quartile (Median) of kurtosis 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.
1.83
Mean skewness among attributes of the numeric type.
9.06
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
84808.14
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
1.9
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.63
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
14.5
Second quartile (Median) of standard deviation of attributes of the numeric type.
31.93
Maximum kurtosis among attributes of the numeric type.
-1.09
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
3154557.66
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
12.7
Third quartile of kurtosis 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.
90.24
Percentage of numeric attributes.
1309.2
Third quartile of means among attributes of the numeric type.
32
The maximum number of distinct values among attributes of the nominal type.
-3.48
Minimum skewness among attributes of the numeric type.
9.76
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
5.65
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3.7
Third quartile of skewness among attributes of the numeric type.
5043959.75
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.05
First quartile of kurtosis among attributes of the numeric type.
4475.88
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1.01
First quartile of means among attributes of the numeric type.
9.43
Standard deviation of the number of distinct values among attributes of the nominal type.
7.72
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.

10 tasks

0 runs - estimation_procedure: Leave one out - target_feature: target_nmae
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
0 runs - estimation_procedure: 50 times Clustering
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