Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2993

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2993

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL2993 (TID: 12239), and it has 647 rows and 66 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.

68 features

pXC50 (target)numeric401 unique values
0 missing
molecule_id (row identifier)nominal647 unique values
0 missing
SssOnumeric361 unique values
0 missing
nArORnumeric5 unique values
0 missing
Eig02_EA.dm.numeric53 unique values
0 missing
NssOnumeric6 unique values
0 missing
Eig05_AEA.dm.numeric454 unique values
0 missing
O.060numeric5 unique values
0 missing
MDDDnumeric449 unique values
0 missing
UNIPnumeric124 unique values
0 missing
CATS2D_02_ALnumeric14 unique values
0 missing
ECCnumeric254 unique values
0 missing
GGI10numeric104 unique values
0 missing
CSInumeric326 unique values
0 missing
P_VSA_e_2numeric505 unique values
0 missing
ICRnumeric268 unique values
0 missing
AECCnumeric360 unique values
0 missing
SMTIVnumeric571 unique values
0 missing
SpMaxA_EA.ri.numeric141 unique values
0 missing
IDEnumeric383 unique values
0 missing
SpMax8_Bh.e.numeric338 unique values
0 missing
SpMax8_Bh.m.numeric356 unique values
0 missing
SpMaxA_EA.dm.numeric129 unique values
0 missing
GGI9numeric151 unique values
0 missing
N.numeric96 unique values
0 missing
SpDiam_AEA.ri.numeric347 unique values
0 missing
SpMax8_Bh.i.numeric335 unique values
0 missing
P_VSA_i_2numeric504 unique values
0 missing
SpMaxA_EA.ed.numeric244 unique values
0 missing
VARnumeric124 unique values
0 missing
ALOGPnumeric517 unique values
0 missing
ALOGP2numeric539 unique values
0 missing
ON0numeric97 unique values
0 missing
MATS3mnumeric293 unique values
0 missing
GMTIVnumeric572 unique values
0 missing
C.017numeric4 unique values
0 missing
nR.Ctnumeric4 unique values
0 missing
Eig13_AEA.dm.numeric392 unique values
0 missing
Eta_epsinumeric372 unique values
0 missing
MSDnumeric443 unique values
0 missing
GATS3vnumeric281 unique values
0 missing
nRCOORnumeric3 unique values
0 missing
Eig14_AEA.dm.numeric400 unique values
0 missing
GGI1numeric16 unique values
0 missing
DECCnumeric342 unique values
0 missing
SpMax8_Bh.s.numeric358 unique values
0 missing
Eig12_AEA.dm.numeric398 unique values
0 missing
ATS2snumeric441 unique values
0 missing
Eig04_AEA.dm.numeric435 unique values
0 missing
SpMin8_Bh.m.numeric357 unique values
0 missing
HVcpxnumeric378 unique values
0 missing
Dznumeric158 unique values
0 missing
CATS2D_09_ALnumeric13 unique values
0 missing
GATS3pnumeric309 unique values
0 missing
JGI8numeric22 unique values
0 missing
SM02_EA.dm.numeric191 unique values
0 missing
Chi1_EA.dm.numeric494 unique values
0 missing
MATS3vnumeric280 unique values
0 missing
MATS3snumeric256 unique values
0 missing
TIC5numeric368 unique values
0 missing
SpMin8_Bh.p.numeric317 unique values
0 missing
SpMax7_Bh.p.numeric323 unique values
0 missing
SpMin8_Bh.v.numeric336 unique values
0 missing
GATS2inumeric313 unique values
0 missing
SpMin1_Bh.i.numeric168 unique values
0 missing
TIC4numeric371 unique values
0 missing
TIC3numeric409 unique values
0 missing
SpMax6_Bh.s.numeric449 unique values
0 missing

62 properties

647
Number of instances (rows) of the dataset.
68
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.
67
Number of numeric attributes.
1
Number of nominal attributes.
236.41
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.
0.19
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.65
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.67
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.35
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
12.85
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
2.08
Third quartile of kurtosis among attributes of the numeric type.
15807.68
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.53
Percentage of numeric attributes.
11.15
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.37
Minimum skewness among attributes of the numeric type.
1.47
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.
0.68
Third quartile of skewness among attributes of the numeric type.
2.17
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.06
First quartile of kurtosis among attributes of the numeric type.
5.08
Third quartile of standard deviation of attributes of the numeric type.
9861.23
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.9
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.49
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.
399.32
Mean of means among attributes of the numeric type.
-0.46
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.27
First quartile of standard deviation of attributes of the numeric type.
-0.17
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.
1.08
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.11
Number of attributes divided by the number of instances.
0.09
Mean skewness among attributes of the numeric type.
2.65
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.

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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