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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3230

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3230

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: CHEMBL3230 (TID: 10809), and it has 573 rows and 43 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Basic Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median).

45 features

pXC50 (target)numeric337 unique values
0 missing
molecule_id (row identifier)nominal573 unique values
0 missing
AMWnumeric432 unique values
0 missing
C.numeric137 unique values
0 missing
H.numeric209 unique values
0 missing
Menumeric94 unique values
0 missing
Minumeric60 unique values
0 missing
Mpnumeric170 unique values
0 missing
Mvnumeric187 unique values
0 missing
MWnumeric445 unique values
0 missing
N.numeric96 unique values
0 missing
nABstring16 unique values
0 missing
nATstring54 unique values
0 missing
nBstring2 unique values
0 missing
nBMstring28 unique values
0 missing
nBOstring28 unique values
0 missing
nBRstring4 unique values
0 missing
nBTstring53 unique values
0 missing
nCstring24 unique values
0 missing
nCLstring5 unique values
0 missing
nCspstring5 unique values
0 missing
nCsp2string25 unique values
0 missing
nCsp3string23 unique values
0 missing
nDBstring10 unique values
0 missing
nFstring7 unique values
0 missing
nHstring39 unique values
0 missing
nHetstring14 unique values
0 missing
nHMstring6 unique values
0 missing
nIstring3 unique values
0 missing
nNstring8 unique values
0 missing
nOstring10 unique values
0 missing
nPstring3 unique values
0 missing
nSstring5 unique values
0 missing
nSKstring28 unique values
0 missing
nTBstring5 unique values
0 missing
nXstring8 unique values
0 missing
O.numeric102 unique values
0 missing
RBFnumeric167 unique values
0 missing
RBNstring22 unique values
0 missing
SCBOnumeric69 unique values
0 missing
Senumeric442 unique values
0 missing
Sinumeric447 unique values
0 missing
Spnumeric428 unique values
0 missing
Svnumeric448 unique values
0 missing
X.numeric73 unique values
0 missing

62 properties

573
Number of instances (rows) of the dataset.
45
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.
18
Number of numeric attributes.
1
Number of nominal attributes.
-0.16
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.08
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
7.48
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.
0.31
Mean skewness among 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.
7.01
Mean standard deviation of attributes of the numeric type.
0.23
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
3.15
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.65
Minimum kurtosis among attributes of the numeric type.
0.13
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
3.45
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
0.56
Third quartile of kurtosis among attributes of the numeric type.
374.1
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
40
Percentage of numeric attributes.
41.68
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-0.37
Minimum skewness among attributes of the numeric type.
2.22
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.
0.01
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.66
Third quartile of skewness among attributes of the numeric type.
1.49
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.57
First quartile of kurtosis among attributes of the numeric type.
7.51
Third quartile of standard deviation of attributes of the numeric type.
58.68
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
1.1
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.26
Mean kurtosis among attributes of the numeric type.
-0.18
First quartile of skewness among attributes of the numeric type.
38.31
Mean of means among attributes of the numeric type.
0.06
First quartile of standard deviation of attributes of the numeric type.
0.11
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among 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.

12 tasks

0 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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