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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2064

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2064

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: CHEMBL2064 (TID: 10227), and it has 15 rows and 117 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.

119 features

pXC50 (target)numeric15 unique values
0 missing
molecule_id (row identifier)nominal15 unique values
0 missing
BIC3numeric12 unique values
0 missing
C.016numeric2 unique values
0 missing
C.019numeric2 unique values
0 missing
CATS2D_02_PLnumeric3 unique values
0 missing
D.Dtr05numeric2 unique values
0 missing
GATS6vnumeric12 unique values
0 missing
JGI4numeric10 unique values
0 missing
MATS1vnumeric12 unique values
0 missing
MATS3inumeric11 unique values
0 missing
MATS6pnumeric12 unique values
0 missing
MATS6vnumeric12 unique values
0 missing
Menumeric9 unique values
0 missing
nCpnumeric4 unique values
0 missing
nCrsnumeric3 unique values
0 missing
NdsCHnumeric2 unique values
0 missing
nR05numeric2 unique values
0 missing
nR.Csnumeric2 unique values
0 missing
S3Knumeric12 unique values
0 missing
SdsCHnumeric2 unique values
0 missing
SpMAD_EA.ri.numeric12 unique values
0 missing
SRW05numeric2 unique values
0 missing
SRW07numeric2 unique values
0 missing
SRW09numeric2 unique values
0 missing
SsNH2numeric8 unique values
0 missing
X1Anumeric11 unique values
0 missing
ATSC3mnumeric12 unique values
0 missing
ATSC4mnumeric12 unique values
0 missing
CIC3numeric12 unique values
0 missing
CIC4numeric12 unique values
0 missing
SpMin2_Bh.s.numeric12 unique values
0 missing
ATS1enumeric12 unique values
0 missing
ATS1inumeric12 unique values
0 missing
ATS2enumeric12 unique values
0 missing
ATS2inumeric12 unique values
0 missing
ATS3enumeric11 unique values
0 missing
ATS3inumeric12 unique values
0 missing
ATS3snumeric12 unique values
0 missing
ATS4enumeric12 unique values
0 missing
ATS4inumeric12 unique values
0 missing
ATS4snumeric12 unique values
0 missing
ATS7inumeric10 unique values
0 missing
ATS8enumeric9 unique values
0 missing
ATS8inumeric9 unique values
0 missing
ATS8pnumeric9 unique values
0 missing
ATS8snumeric9 unique values
0 missing
ATS8vnumeric9 unique values
0 missing
ATSC1inumeric12 unique values
0 missing
ATSC2inumeric12 unique values
0 missing
ATSC4vnumeric12 unique values
0 missing
ATSC8vnumeric9 unique values
0 missing
BIC4numeric12 unique values
0 missing
BIC5numeric12 unique values
0 missing
Chi0_EA.dm.numeric12 unique values
0 missing
Chi1_EA.bo.numeric12 unique values
0 missing
CIC5numeric12 unique values
0 missing
DECCnumeric12 unique values
0 missing
Eig09_AEA.bo.numeric7 unique values
0 missing
Eig10_AEA.bo.numeric9 unique values
0 missing
Eta_Cnumeric12 unique values
0 missing
Eta_Lnumeric12 unique values
0 missing
IDEnumeric12 unique values
0 missing
ISIZnumeric12 unique values
0 missing
LOCnumeric12 unique values
0 missing
MSDnumeric12 unique values
0 missing
nATnumeric12 unique values
0 missing
nBTnumeric12 unique values
0 missing
ON0Vnumeric12 unique values
0 missing
PHInumeric12 unique values
0 missing
P_VSA_i_3numeric11 unique values
0 missing
Senumeric12 unique values
0 missing
Sinumeric12 unique values
0 missing
SIC3numeric12 unique values
0 missing
SIC4numeric12 unique values
0 missing
SIC5numeric12 unique values
0 missing
SpMax1_Bh.p.numeric10 unique values
0 missing
SpMax4_Bh.e.numeric12 unique values
0 missing
SpMax4_Bh.i.numeric12 unique values
0 missing
SpMax6_Bh.e.numeric12 unique values
0 missing
SpMax6_Bh.i.numeric12 unique values
0 missing
SpMax6_Bh.p.numeric12 unique values
0 missing
SpMax6_Bh.v.numeric12 unique values
0 missing
SpMax8_Bh.i.numeric11 unique values
0 missing
SpMin1_Bh.s.numeric11 unique values
0 missing
SpMin4_Bh.p.numeric12 unique values
0 missing
SpMin4_Bh.v.numeric12 unique values
0 missing
SpMin5_Bh.e.numeric12 unique values
0 missing
SpMin5_Bh.v.numeric12 unique values
0 missing
SpMin6_Bh.e.numeric11 unique values
0 missing
SpMin6_Bh.i.numeric9 unique values
0 missing
SpMin6_Bh.p.numeric12 unique values
0 missing
SpMin6_Bh.v.numeric12 unique values
0 missing
SpMin8_Bh.m.numeric9 unique values
0 missing
SpMin8_Bh.p.numeric11 unique values
0 missing
SpMin8_Bh.v.numeric11 unique values
0 missing
TIC2numeric12 unique values
0 missing
CATS2D_02_NLnumeric4 unique values
0 missing
Eig09_EAnumeric6 unique values
0 missing
Eig09_EA.ed.numeric10 unique values
0 missing
Eig09_EA.ri.numeric8 unique values
0 missing
Eig10_AEA.dm.numeric10 unique values
0 missing
Eig10_EAnumeric8 unique values
0 missing
Eig10_EA.bo.numeric10 unique values
0 missing
Eig10_EA.ed.numeric8 unique values
0 missing
Eig10_EA.ri.numeric8 unique values
0 missing
MATS6inumeric11 unique values
0 missing
RBNnumeric8 unique values
0 missing
SdssCnumeric8 unique values
0 missing
SM03_AEA.dm.numeric6 unique values
0 missing
SM04_AEA.dm.numeric8 unique values
0 missing
SM04_AEA.ri.numeric10 unique values
0 missing
SM05_AEA.ri.numeric8 unique values
0 missing
SpDiam_AEA.ri.numeric11 unique values
0 missing
SpMin1_Bh.m.numeric10 unique values
0 missing
SpMin1_Bh.p.numeric11 unique values
0 missing
SsssCHnumeric10 unique values
0 missing
MATS1pnumeric12 unique values
0 missing
SM02_EA.ed.numeric11 unique values
0 missing

62 properties

15
Number of instances (rows) of the dataset.
119
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.
118
Number of numeric attributes.
1
Number of nominal attributes.
-0.36
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.
9.08
Mean of means among attributes of the numeric type.
0.02
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.38
First quartile of standard deviation of attributes of the numeric type.
-0.84
Average class difference between consecutive instances.
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.
Entropy of the target attribute values.
Average number of distinct values among the attributes of the nominal type.
-0.94
Second quartile (Median) of kurtosis among attributes of the numeric type.
7.93
Number of attributes divided by the number of instances.
0.42
Mean skewness among attributes of the numeric type.
1.29
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.
5.5
Mean standard deviation of 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.
Minimal entropy among attributes.
0.36
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
-2.08
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.65
Second quartile (Median) of standard deviation of attributes of the numeric type.
7.96
Maximum kurtosis among attributes of the numeric type.
-1.46
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
291.09
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.
0.41
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.
99.16
Percentage of numeric attributes.
4.34
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.62
Minimum skewness among attributes of the numeric type.
0.84
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
1.75
Maximum skewness among attributes of the numeric type.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.98
Third quartile of skewness among attributes of the numeric type.
148.77
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-1.33
First quartile of kurtosis among attributes of the numeric type.
2.21
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.
0.48
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal 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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