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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4175

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4175

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL4175 (TID: 11868), and it has 519 rows and 68 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.

70 features

pXC50 (target)numeric29 unique values
0 missing
Chi1_EA.ri.numeric497 unique values
0 missing
ATS5enumeric423 unique values
0 missing
ATS3inumeric398 unique values
0 missing
ATS4mnumeric410 unique values
0 missing
P_VSA_LogP_7numeric94 unique values
0 missing
SssOnumeric170 unique values
0 missing
SpMaxA_EA.ri.numeric105 unique values
0 missing
Psi_e_0numeric479 unique values
0 missing
SpMin7_Bh.s.numeric247 unique values
0 missing
VvdwZAZnumeric474 unique values
0 missing
MWnumeric463 unique values
0 missing
SpMin7_Bh.p.numeric331 unique values
0 missing
P_VSA_i_3numeric310 unique values
0 missing
ON0Vnumeric398 unique values
0 missing
SM03_AEA.dm.numeric334 unique values
0 missing
Eig09_EAnumeric334 unique values
0 missing
SpMax8_Bh.m.numeric327 unique values
0 missing
Chi1_EA.bo.numeric462 unique values
0 missing
SpMin7_Bh.m.numeric313 unique values
0 missing
S3Knumeric466 unique values
0 missing
SpMin5_Bh.s.numeric324 unique values
0 missing
ATSC4mnumeric508 unique values
0 missing
nRNR2numeric3 unique values
0 missing
GGI8numeric281 unique values
0 missing
SM02_AEA.dm.numeric363 unique values
0 missing
Eig08_EAnumeric363 unique values
0 missing
SpMin7_Bh.v.numeric326 unique values
0 missing
TIC1numeric472 unique values
0 missing
Xunumeric475 unique values
0 missing
IDMTnumeric476 unique values
0 missing
IDETnumeric475 unique values
0 missing
ATS2enumeric394 unique values
0 missing
TIC2numeric478 unique values
0 missing
ZM2Madnumeric504 unique values
0 missing
ATS7mnumeric443 unique values
0 missing
Eig06_AEA.dm.numeric395 unique values
0 missing
Eig09_AEA.dm.numeric381 unique values
0 missing
Eig05_AEA.dm.numeric408 unique values
0 missing
Eig10_AEA.dm.numeric351 unique values
0 missing
Eig07_AEA.dm.numeric383 unique values
0 missing
ATS5inumeric425 unique values
0 missing
SsssNnumeric117 unique values
0 missing
Eta_Lnumeric476 unique values
0 missing
ATS3mnumeric392 unique values
0 missing
CATS2D_02_ALnumeric15 unique values
0 missing
Eta_Cnumeric510 unique values
0 missing
Eig08_AEA.dm.numeric375 unique values
0 missing
Chi1_EA.dm.numeric462 unique values
0 missing
TIC0numeric451 unique values
0 missing
IACnumeric451 unique values
0 missing
ATSC3mnumeric501 unique values
0 missing
Chi0_EA.dm.numeric453 unique values
0 missing
Eig12_AEA.dm.numeric351 unique values
0 missing
P_VSA_p_1numeric94 unique values
0 missing
ATSC5mnumeric510 unique values
0 missing
ATS2mnumeric380 unique values
0 missing
CENTnumeric425 unique values
0 missing
C.006numeric10 unique values
0 missing
ATS2inumeric387 unique values
0 missing
N.068numeric3 unique values
0 missing
P_VSA_MR_1numeric78 unique values
0 missing
molecule_id (row identifier)nominal519 unique values
0 missing
ATS1mnumeric364 unique values
0 missing
SM03_AEA.ri.numeric415 unique values
0 missing
Eig08_EA.ed.numeric415 unique values
0 missing
S1Knumeric420 unique values
0 missing
Eig05_EA.dm.numeric20 unique values
0 missing
ATSC2mnumeric485 unique values
0 missing
ATS8mnumeric433 unique values
0 missing

62 properties

519
Number of instances (rows) of the dataset.
70
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.
69
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.
98.57
Percentage of numeric attributes.
1.43
Percentage of nominal attributes.
First quartile of entropy among attributes.
0.04
First quartile of kurtosis among attributes of the numeric type.
1.4
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.2
First quartile of skewness among attributes of the numeric type.
0.35
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.56
Second quartile (Median) of kurtosis among attributes of the numeric type.
4.42
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.
0.47
Second quartile (Median) of skewness among attributes of the numeric type.
1.33
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
1.89
Third quartile of kurtosis among attributes of the numeric type.
24.35
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.83
Third quartile of skewness among attributes of the numeric type.
9.03
Third quartile of standard deviation of attributes of the numeric type.
0.8
Average class difference between consecutive instances.
364.76
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.13
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.
11.74
Maximum kurtosis among attributes of the numeric type.
19886.04
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.
3.41
Maximum skewness among attributes of the numeric type.
14392.37
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
1.51
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.
0.35
Mean skewness among attributes of the numeric type.
242.95
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-0.76
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.
-2.13
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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