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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2634

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2634

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 by unknown
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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: CHEMBL2634 (TID: 10844), and it has 166 rows and 67 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.

69 features

pXC50 (target)numeric76 unique values
0 missing
SpMin8_Bh.i.numeric109 unique values
0 missing
RBFnumeric76 unique values
0 missing
SpMax1_Bh.m.numeric126 unique values
0 missing
ATS4enumeric157 unique values
0 missing
nRNHOnumeric2 unique values
0 missing
ATSC7vnumeric162 unique values
0 missing
SM02_AEA.ri.numeric146 unique values
0 missing
Eig07_EA.ed.numeric146 unique values
0 missing
Eig07_AEA.ed.numeric136 unique values
0 missing
SM04_EA.ri.numeric150 unique values
0 missing
SpMaxA_EA.dm.numeric67 unique values
0 missing
ATSC3inumeric158 unique values
0 missing
ATSC2inumeric151 unique values
0 missing
ATSC1inumeric142 unique values
0 missing
SM05_EA.ri.numeric151 unique values
0 missing
ATS4inumeric156 unique values
0 missing
X1Anumeric45 unique values
0 missing
SpMax4_Bh.m.numeric142 unique values
0 missing
SM03_AEA.ed.numeric137 unique values
0 missing
Eig05_AEA.bo.numeric134 unique values
0 missing
SpMin4_Bh.p.numeric132 unique values
0 missing
SpMin3_Bh.i.numeric138 unique values
0 missing
SpMax4_Bh.p.numeric133 unique values
0 missing
ZM1Madnumeric162 unique values
0 missing
Eig04_EA.ri.numeric145 unique values
0 missing
Eig04_AEA.ri.numeric147 unique values
0 missing
ATS7inumeric157 unique values
0 missing
ATS5inumeric153 unique values
0 missing
SpMin6_Bh.p.numeric131 unique values
0 missing
SM06_EAnumeric142 unique values
0 missing
TPCnumeric143 unique values
0 missing
SpMin4_Bh.e.numeric134 unique values
0 missing
ATS8inumeric161 unique values
0 missing
ATS8enumeric159 unique values
0 missing
ATSC3mnumeric162 unique values
0 missing
ATSC6mnumeric164 unique values
0 missing
SpMin7_Bh.m.numeric113 unique values
0 missing
SpMin7_Bh.e.numeric117 unique values
0 missing
SpMax2_Bh.i.numeric117 unique values
0 missing
MCDnumeric101 unique values
0 missing
ON1Vnumeric154 unique values
0 missing
SM12_AEA.ri.numeric131 unique values
0 missing
Eig02_EA.bo.numeric131 unique values
0 missing
SpMax2_Bh.e.numeric118 unique values
0 missing
SM11_AEA.dm.numeric146 unique values
0 missing
Eig02_EA.ed.numeric146 unique values
0 missing
SM10_AEA.bo.numeric132 unique values
0 missing
Eig02_EAnumeric132 unique values
0 missing
Eig02_AEA.bo.numeric128 unique values
0 missing
Eig02_EA.ri.numeric138 unique values
0 missing
Eig02_AEA.ri.numeric145 unique values
0 missing
SpMax6_Bh.i.numeric133 unique values
0 missing
SM06_EA.ri.numeric150 unique values
0 missing
ATSC4inumeric159 unique values
0 missing
SpMin5_Bh.m.numeric129 unique values
0 missing
ATSC8mnumeric165 unique values
0 missing
Eig02_AEA.ed.numeric137 unique values
0 missing
GGI5numeric130 unique values
0 missing
SpMin4_Bh.i.numeric135 unique values
0 missing
ATS3inumeric155 unique values
0 missing
molecule_id (row identifier)nominal166 unique values
0 missing
SM03_EA.ri.numeric131 unique values
0 missing
PW4numeric67 unique values
0 missing
GATS2vnumeric139 unique values
0 missing
GATS2pnumeric128 unique values
0 missing
SpMin6_Bh.m.numeric123 unique values
0 missing
SpMin7_Bh.p.numeric119 unique values
0 missing
SpMin5_Bh.s.numeric111 unique values
0 missing

62 properties

166
Number of instances (rows) of the dataset.
69
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.
68
Number of numeric attributes.
1
Number of nominal attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
98.55
Percentage of numeric attributes.
1.45
Percentage of nominal attributes.
First quartile of entropy among attributes.
0.14
First quartile of kurtosis among attributes of the numeric type.
1.39
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.96
First quartile of skewness among attributes of the numeric type.
0.24
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.47
Second quartile (Median) of kurtosis among attributes of the numeric type.
3.45
Second quartile (Median) of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
-0.52
Second quartile (Median) of skewness among attributes of the numeric type.
0.38
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
1.06
Third quartile of kurtosis among attributes of the numeric type.
4.98
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
-0.01
Third quartile of skewness among attributes of the numeric type.
0.56
Third quartile of standard deviation of attributes of the numeric type.
0.38
Average class difference between consecutive instances.
7.18
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.42
Number of attributes divided by the number of instances.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
27.01
Maximum kurtosis among attributes of the numeric type.
186.88
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
5.14
Maximum skewness among attributes of the numeric type.
58.41
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
1.04
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
Average mutual information between the nominal attributes and the target attribute.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Average number of distinct values among the attributes of the nominal type.
-0.32
Mean skewness among attributes of the numeric type.
1.9
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-0.62
Minimum kurtosis among attributes of the numeric type.
0.06
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-1.7
Minimum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.

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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