Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3009

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3009

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: CHEMBL3009 (TID: 12699), and it has 789 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)numeric94 unique values
0 missing
molecule_id (row identifier)nominal789 unique values
0 missing
Chi1_EA.dm.numeric681 unique values
0 missing
Chi0_EA.dm.numeric676 unique values
0 missing
ATS7mnumeric614 unique values
0 missing
SpMax8_Bh.m.numeric458 unique values
0 missing
Eig10_EAnumeric474 unique values
0 missing
SM04_AEA.dm.numeric474 unique values
0 missing
ATS1mnumeric509 unique values
0 missing
MWnumeric697 unique values
0 missing
S2Knumeric680 unique values
0 missing
XMODnumeric757 unique values
0 missing
ATS8mnumeric614 unique values
0 missing
MDDDnumeric696 unique values
0 missing
nPyrimidinesnumeric3 unique values
0 missing
X1solnumeric616 unique values
0 missing
PHInumeric677 unique values
0 missing
X1vnumeric733 unique values
0 missing
ON1numeric237 unique values
0 missing
Neoplastic.80numeric2 unique values
0 missing
Chi0_EA.ri.numeric751 unique values
0 missing
Eig11_EAnumeric472 unique values
0 missing
SM05_AEA.dm.numeric472 unique values
0 missing
Chi0_EA.ed.numeric686 unique values
0 missing
X0solnumeric461 unique values
0 missing
Eig11_AEA.dm.numeric500 unique values
0 missing
VARnumeric210 unique values
0 missing
Eta_alphanumeric489 unique values
0 missing
ATSC3mnumeric767 unique values
0 missing
S1Knumeric631 unique values
0 missing
AMRnumeric759 unique values
0 missing
IVDMnumeric290 unique values
0 missing
Eig11_AEA.ri.numeric520 unique values
0 missing
Eig10_AEA.ri.numeric534 unique values
0 missing
Eig10_AEA.dm.numeric522 unique values
0 missing
SpMin7_Bh.i.numeric420 unique values
0 missing
Eig09_AEA.dm.numeric535 unique values
0 missing
SpMin7_Bh.e.numeric422 unique values
0 missing
SpMax7_Bh.m.numeric460 unique values
0 missing
Infective.80numeric2 unique values
0 missing
Eig10_AEA.bo.numeric493 unique values
0 missing
IDETnumeric709 unique values
0 missing
X2solnumeric668 unique values
0 missing
ECCnumeric385 unique values
0 missing
DLS_02numeric5 unique values
0 missing
X1numeric559 unique values
0 missing
Eig07_AEA.dm.numeric547 unique values
0 missing
SpMaxA_EA.ri.numeric122 unique values
0 missing
Chi0_AEA.bo.numeric547 unique values
0 missing
Chi0_AEA.dm.numeric547 unique values
0 missing
Chi0_AEA.ed.numeric547 unique values
0 missing
Chi0_AEA.ri.numeric547 unique values
0 missing
Chi0_EAnumeric547 unique values
0 missing
Eig15_AEA.bo.numeric508 unique values
0 missing
ICRnumeric430 unique values
0 missing
Chi1_EA.ri.numeric745 unique values
0 missing
Chi1_EA.ed.numeric671 unique values
0 missing
Eta_betaSnumeric94 unique values
0 missing
Dznumeric253 unique values
0 missing
Chi0_EA.bo.numeric666 unique values
0 missing
VvdwZAZnumeric723 unique values
0 missing
LPRSnumeric712 unique values
0 missing
X0vnumeric719 unique values
0 missing
Eta_Lnumeric709 unique values
0 missing
Eig07_EAnumeric485 unique values
0 missing
SM15_AEA.bo.numeric485 unique values
0 missing
IACnumeric678 unique values
0 missing
TIC0numeric678 unique values
0 missing
S3Knumeric697 unique values
0 missing
Xunumeric700 unique values
0 missing
SpMax8_Bh.v.numeric427 unique values
0 missing

62 properties

789
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.
0.09
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.92
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.
0.28
Mean skewness among attributes of the numeric type.
7.01
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
23.02
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.
0.77
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.1
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
2.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
17.02
Maximum kurtosis among attributes of the numeric type.
0.11
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
1488.25
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.
2.28
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.
19.04
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.05
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.
2.89
Maximum skewness among attributes of the numeric type.
0.03
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.88
Third quartile of skewness among attributes of the numeric type.
917.09
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.55
First quartile of kurtosis among attributes of the numeric type.
4.68
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.
1.67
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
2.61
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.
53.13
Mean of means among attributes of the numeric type.
-0.7
First quartile of skewness among attributes of the numeric type.
0.62
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.52
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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