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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3396

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3396

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by Noureddin Sadawi
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This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL3396 (TID: 12026), and it has 24 rows and 43 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Basic Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median).

45 features

pXC50 (target)numeric12 unique values
0 missing
molecule_id (row identifier)nominal24 unique values
0 missing
AMWnumeric20 unique values
0 missing
C.numeric19 unique values
0 missing
H.numeric16 unique values
0 missing
Menumeric16 unique values
0 missing
Minumeric12 unique values
0 missing
Mpnumeric17 unique values
0 missing
Mvnumeric17 unique values
0 missing
MWnumeric20 unique values
0 missing
N.numeric17 unique values
0 missing
nABnumeric4 unique values
0 missing
nATnumeric18 unique values
0 missing
nBnumeric1 unique values
0 missing
nBMnumeric7 unique values
0 missing
nBOnumeric14 unique values
0 missing
nBRnumeric1 unique values
0 missing
nBTnumeric17 unique values
0 missing
nCnumeric11 unique values
0 missing
nCLnumeric1 unique values
0 missing
nCspnumeric1 unique values
0 missing
nCsp2numeric6 unique values
0 missing
nCsp3numeric11 unique values
0 missing
nDBnumeric6 unique values
0 missing
nFnumeric2 unique values
0 missing
nHnumeric14 unique values
0 missing
nHetnumeric6 unique values
0 missing
nHMnumeric2 unique values
0 missing
nInumeric1 unique values
0 missing
nNnumeric5 unique values
0 missing
nOnumeric5 unique values
0 missing
nPnumeric1 unique values
0 missing
nSnumeric2 unique values
0 missing
nSKnumeric12 unique values
0 missing
nTBnumeric1 unique values
0 missing
nXnumeric2 unique values
0 missing
O.numeric18 unique values
0 missing
RBFnumeric17 unique values
0 missing
RBNnumeric7 unique values
0 missing
SCBOnumeric14 unique values
0 missing
Senumeric20 unique values
0 missing
Sinumeric20 unique values
0 missing
Spnumeric20 unique values
0 missing
Svnumeric20 unique values
0 missing
X.numeric14 unique values
0 missing

62 properties

24
Number of instances (rows) of the dataset.
45
Number of attributes (columns) of the dataset.
0
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.
44
Number of numeric attributes.
1
Number of nominal attributes.
1.57
Second quartile (Median) of kurtosis among attributes of the numeric type.
1.88
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.28
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.
0.47
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
3.99
Mean standard deviation of attributes of the numeric type.
0.26
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
1.7
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.2
Minimum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
24
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
5.69
Third quartile of kurtosis among attributes of the numeric type.
452.95
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
97.78
Percentage of numeric attributes.
36.2
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-3.22
Minimum skewness among attributes of the numeric type.
2.22
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.56
Third quartile of skewness among attributes of the numeric type.
4.9
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.43
First quartile of kurtosis among attributes of the numeric type.
4.38
Third quartile of standard deviation of attributes of the numeric type.
65.72
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.65
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
3.72
Mean kurtosis among attributes of the numeric type.
-0.21
First quartile of skewness among attributes of the numeric type.
25.76
Mean of means among attributes of the numeric type.
0.02
First quartile of standard deviation of attributes of the numeric type.
0.6
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
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.

12 tasks

1 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
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
0 runs - estimation_procedure: 50 times Clustering
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