Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4045

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4045

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL4045 (TID: 11364), and it has 969 rows and 69 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

71 features

pXC50 (target)numeric76 unique values
0 missing
molecule_id (row identifier)nominal969 unique values
0 missing
SpMax4_Bh.m.numeric561 unique values
0 missing
ATS2mnumeric602 unique values
0 missing
MWnumeric847 unique values
0 missing
X0solnumeric543 unique values
0 missing
SpMax5_Bh.m.numeric571 unique values
0 missing
X0vnumeric871 unique values
0 missing
ATS1mnumeric574 unique values
0 missing
Eig06_EA.ed.numeric779 unique values
0 missing
SM15_AEA.dm.numeric779 unique values
0 missing
GMTIVnumeric941 unique values
0 missing
SpMax3_Bh.m.numeric453 unique values
0 missing
X2solnumeric813 unique values
0 missing
ATS7mnumeric729 unique values
0 missing
Eta_alphanumeric587 unique values
0 missing
Eig06_AEA.dm.numeric687 unique values
0 missing
XMODnumeric921 unique values
0 missing
ZM2Madnumeric938 unique values
0 missing
S1Knumeric738 unique values
0 missing
X1solnumeric750 unique values
0 missing
Eig09_AEA.dm.numeric632 unique values
0 missing
X2vnumeric898 unique values
0 missing
IACnumeric819 unique values
0 missing
SpMaxA_EA.bo.numeric183 unique values
0 missing
TIC0numeric819 unique values
0 missing
AMRnumeric925 unique values
0 missing
SMTIVnumeric931 unique values
0 missing
ATS6mnumeric704 unique values
0 missing
X1vnumeric887 unique values
0 missing
X5solnumeric818 unique values
0 missing
Eig10_AEA.dm.numeric625 unique values
0 missing
ATS8mnumeric729 unique values
0 missing
VvdwMGnumeric800 unique values
0 missing
Vxnumeric800 unique values
0 missing
Eig05_EAnumeric597 unique values
0 missing
SM13_AEA.bo.numeric597 unique values
0 missing
Chi1_EA.bo.numeric839 unique values
0 missing
IDETnumeric870 unique values
0 missing
IDMTnumeric872 unique values
0 missing
LPRSnumeric874 unique values
0 missing
SpAD_AEA.dm.numeric918 unique values
0 missing
Xunumeric856 unique values
0 missing
MDDDnumeric843 unique values
0 missing
PHInumeric814 unique values
0 missing
X3solnumeric827 unique values
0 missing
Chi1_EA.ri.numeric912 unique values
0 missing
Eig06_EAnumeric589 unique values
0 missing
SM14_AEA.bo.numeric589 unique values
0 missing
Eig06_AEA.ri.numeric665 unique values
0 missing
Eig06_AEA.ed.numeric662 unique values
0 missing
VvdwZAZnumeric874 unique values
0 missing
Eig12_EA.bo.numeric627 unique values
0 missing
ZM1Pernumeric932 unique values
0 missing
Eig11_EA.bo.numeric627 unique values
0 missing
SMTInumeric857 unique values
0 missing
Eig12_AEA.dm.numeric606 unique values
0 missing
BIDnumeric149 unique values
0 missing
Psi_i_0numeric889 unique values
0 missing
Eig04_EAnumeric566 unique values
0 missing
HDcpxnumeric271 unique values
0 missing
IDMnumeric728 unique values
0 missing
SM12_AEA.bo.numeric566 unique values
0 missing
X3vnumeric866 unique values
0 missing
Eta_Cnumeric937 unique values
0 missing
Eig10_EA.ri.numeric632 unique values
0 missing
Uindexnumeric860 unique values
0 missing
X2numeric818 unique values
0 missing
Eig04_AEA.bo.numeric556 unique values
0 missing
Eig09_EA.ri.numeric624 unique values
0 missing
X4vnumeric836 unique values
0 missing

62 properties

969
Number of instances (rows) of the dataset.
71
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.
70
Number of numeric attributes.
1
Number of nominal 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.
Second quartile (Median) of entropy among attributes.
0.07
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.2
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.
0.14
Mean skewness among attributes of the numeric type.
6.93
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
907.16
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.
0.42
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.22
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.93
Second quartile (Median) of standard deviation of attributes of the numeric type.
65.67
Maximum kurtosis among attributes of the numeric type.
0.16
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
31648.62
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.
3.57
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
98.59
Percentage of numeric attributes.
43.35
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.51
Minimum skewness among attributes of the numeric type.
1.41
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
3.31
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.59
Third quartile of skewness among attributes of the numeric type.
23355.92
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.45
First quartile of kurtosis among attributes of the numeric type.
13.97
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.
3.11
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
4.21
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.
1206.41
Mean of means among attributes of the numeric type.
-0.87
First quartile of skewness among attributes of the numeric type.
0.36
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.53
First quartile of standard deviation of attributes of the numeric type.

12 tasks

2 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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