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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741214

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741214

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: CHEMBL1741214 (TID: 104010), and it has 41 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)numeric27 unique values
0 missing
molecule_id (row identifier)nominal41 unique values
0 missing
AMWnumeric41 unique values
0 missing
C.numeric33 unique values
0 missing
H.numeric38 unique values
0 missing
Menumeric31 unique values
0 missing
Minumeric28 unique values
0 missing
Mpnumeric37 unique values
0 missing
Mvnumeric37 unique values
0 missing
MWnumeric41 unique values
0 missing
N.numeric29 unique values
0 missing
nABnumeric11 unique values
0 missing
nATnumeric24 unique values
0 missing
nBnumeric1 unique values
0 missing
nBMnumeric17 unique values
0 missing
nBOnumeric17 unique values
0 missing
nBRnumeric2 unique values
0 missing
nBTnumeric24 unique values
0 missing
nCnumeric14 unique values
0 missing
nCLnumeric3 unique values
0 missing
nCspnumeric2 unique values
0 missing
nCsp2numeric13 unique values
0 missing
nCsp3numeric13 unique values
0 missing
nDBnumeric6 unique values
0 missing
nFnumeric3 unique values
0 missing
nHnumeric20 unique values
0 missing
nHetnumeric10 unique values
0 missing
nHMnumeric4 unique values
0 missing
nInumeric1 unique values
0 missing
nNnumeric7 unique values
0 missing
nOnumeric6 unique values
0 missing
nPnumeric1 unique values
0 missing
nSnumeric4 unique values
0 missing
nSKnumeric16 unique values
0 missing
nTBnumeric2 unique values
0 missing
nXnumeric4 unique values
0 missing
O.numeric29 unique values
0 missing
RBFnumeric32 unique values
0 missing
RBNnumeric9 unique values
0 missing
SCBOnumeric23 unique values
0 missing
Senumeric41 unique values
0 missing
Sinumeric41 unique values
0 missing
Spnumeric41 unique values
0 missing
Svnumeric41 unique values
0 missing
X.numeric13 unique values
0 missing

62 properties

41
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.
44
Number of numeric attributes.
1
Number of nominal attributes.
0.05
Second quartile (Median) of kurtosis among attributes of the numeric type.
1.1
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.56
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.
0.95
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.
4.27
Mean standard deviation of attributes of the numeric type.
0.5
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.
2.1
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.38
Minimum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
41
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
1.07
Third quartile of kurtosis among attributes of the numeric type.
324.65
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
97.78
Percentage of numeric attributes.
23.98
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-0.99
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
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.19
Third quartile of skewness among attributes of the numeric type.
6.4
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.47
First quartile of kurtosis among attributes of the numeric type.
4.75
Third quartile of standard deviation of attributes of the numeric type.
60.07
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0.59
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.
3.8
Mean kurtosis among attributes of the numeric type.
0.08
First quartile of skewness among attributes of the numeric type.
19.03
Mean of means among attributes of the numeric type.
0.22
First quartile of standard deviation of attributes of the numeric type.
0.46
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

1 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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