Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1795098

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1795098

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: CHEMBL1795098 (TID: 104180), and it has 1010 rows and 71 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.

73 features

pXC50 (target)numeric648 unique values
0 missing
molecule_id (row identifier)nominal1010 unique values
0 missing
P_VSA_s_6numeric652 unique values
0 missing
P_VSA_v_2numeric735 unique values
0 missing
P_VSA_p_2numeric692 unique values
0 missing
Eig05_EA.bo.numeric662 unique values
0 missing
SM15_AEA.ri.numeric662 unique values
0 missing
SpMax8_Bh.s.numeric623 unique values
0 missing
MATS1vnumeric190 unique values
0 missing
SpMax5_Bh.s.numeric576 unique values
0 missing
SAaccnumeric726 unique values
0 missing
SPInumeric946 unique values
0 missing
Eig06_AEA.bo.numeric626 unique values
0 missing
Eig06_EA.bo.numeric676 unique values
0 missing
SpMax7_Bh.s.numeric664 unique values
0 missing
P_VSA_e_5numeric225 unique values
0 missing
P_VSA_m_3numeric283 unique values
0 missing
Eig05_AEA.dm.numeric681 unique values
0 missing
Eig04_EA.ed.numeric840 unique values
0 missing
SM13_AEA.dm.numeric840 unique values
0 missing
BACnumeric94 unique values
0 missing
Eig09_AEA.ed.numeric659 unique values
0 missing
GATS2snumeric367 unique values
0 missing
PCDnumeric844 unique values
0 missing
SpMAD_AEA.dm.numeric267 unique values
0 missing
piIDnumeric900 unique values
0 missing
Uinumeric34 unique values
0 missing
TPSA.Tot.numeric740 unique values
0 missing
piPC04numeric662 unique values
0 missing
piPC05numeric718 unique values
0 missing
Eig03_EA.ed.numeric837 unique values
0 missing
SM12_AEA.dm.numeric837 unique values
0 missing
Eig08_AEA.bo.numeric575 unique values
0 missing
piPC06numeric770 unique values
0 missing
AACnumeric508 unique values
0 missing
AECCnumeric754 unique values
0 missing
ALOGPnumeric883 unique values
0 missing
ALOGP2numeric959 unique values
0 missing
AMRnumeric969 unique values
0 missing
AMWnumeric823 unique values
0 missing
ARRnumeric180 unique values
0 missing
ATS1enumeric570 unique values
0 missing
ATS1inumeric561 unique values
0 missing
ATS1mnumeric582 unique values
0 missing
ATS1pnumeric542 unique values
0 missing
ATS1snumeric560 unique values
0 missing
ATS1vnumeric545 unique values
0 missing
ATS2enumeric600 unique values
0 missing
ATS2inumeric619 unique values
0 missing
ATS2mnumeric601 unique values
0 missing
ATS2pnumeric567 unique values
0 missing
ATS2snumeric627 unique values
0 missing
ATS2vnumeric576 unique values
0 missing
ATS3enumeric635 unique values
0 missing
ATS3inumeric665 unique values
0 missing
ATS3mnumeric629 unique values
0 missing
ATS3pnumeric624 unique values
0 missing
ATS3snumeric615 unique values
0 missing
ATS3vnumeric635 unique values
0 missing
ATS4enumeric670 unique values
0 missing
ATS4inumeric698 unique values
0 missing
ATS4mnumeric651 unique values
0 missing
ATS4pnumeric673 unique values
0 missing
ATS4snumeric669 unique values
0 missing
ATS4vnumeric657 unique values
0 missing
ATS5enumeric704 unique values
0 missing
ATS5inumeric723 unique values
0 missing
ATS5mnumeric698 unique values
0 missing
ATS5pnumeric693 unique values
0 missing
ATS5snumeric710 unique values
0 missing
ATS5vnumeric708 unique values
0 missing
ATS6enumeric740 unique values
0 missing
ATS6inumeric748 unique values
0 missing

62 properties

1010
Number of instances (rows) of the dataset.
73
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.
72
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.
0.07
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
1.56
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.
-0.23
Mean skewness among attributes of the numeric type.
4.5
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
6.07
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.
-0.36
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
0.02
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.39
Second quartile (Median) of standard deviation of attributes of the numeric type.
25.07
Maximum kurtosis among attributes of the numeric type.
0.02
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
128.96
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.
7.22
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.
98.63
Percentage of numeric attributes.
6.58
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.96
Minimum skewness among attributes of the numeric type.
1.37
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
3.28
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.04
Third quartile of skewness among attributes of the numeric type.
53.3
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.09
First quartile of kurtosis among attributes of the numeric type.
1.13
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.
3.66
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
3.68
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.
16.81
Mean of means among attributes of the numeric type.
-0.62
First quartile of skewness among attributes of the numeric type.
0.65
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.27
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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