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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1075108

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1075108

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: CHEMBL1075108 (TID: 103158), and it has 53 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)numeric31 unique values
0 missing
molecule_id (row identifier)nominal53 unique values
0 missing
AMWnumeric32 unique values
0 missing
C.numeric21 unique values
0 missing
H.numeric25 unique values
0 missing
Menumeric16 unique values
0 missing
Minumeric19 unique values
0 missing
Mpnumeric26 unique values
0 missing
Mvnumeric28 unique values
0 missing
MWnumeric32 unique values
0 missing
N.numeric14 unique values
0 missing
nABnumeric5 unique values
0 missing
nATnumeric15 unique values
0 missing
nBnumeric1 unique values
0 missing
nBMnumeric7 unique values
0 missing
nBOnumeric12 unique values
0 missing
nBRnumeric2 unique values
0 missing
nBTnumeric15 unique values
0 missing
nCnumeric10 unique values
0 missing
nCLnumeric2 unique values
0 missing
nCspnumeric2 unique values
0 missing
nCsp2numeric6 unique values
0 missing
nCsp3numeric6 unique values
0 missing
nDBnumeric4 unique values
0 missing
nFnumeric5 unique values
0 missing
nHnumeric10 unique values
0 missing
nHetnumeric6 unique values
0 missing
nHMnumeric2 unique values
0 missing
nInumeric1 unique values
0 missing
nNnumeric2 unique values
0 missing
nOnumeric4 unique values
0 missing
nPnumeric1 unique values
0 missing
nSnumeric2 unique values
0 missing
nSKnumeric11 unique values
0 missing
nTBnumeric2 unique values
0 missing
nXnumeric5 unique values
0 missing
O.numeric21 unique values
0 missing
RBFnumeric24 unique values
0 missing
RBNnumeric5 unique values
0 missing
SCBOnumeric17 unique values
0 missing
Senumeric32 unique values
0 missing
Sinumeric32 unique values
0 missing
Spnumeric32 unique values
0 missing
Svnumeric32 unique values
0 missing
X.numeric7 unique values
0 missing

62 properties

53
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.
2.28
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.
0.02
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
-0.91
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
1.1
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
53
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
4.7
Third quartile of kurtosis among attributes of the numeric type.
359.78
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.
27.7
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-1.96
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.
1.65
Third quartile of skewness among attributes of the numeric type.
7.28
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
1.02
First quartile of kurtosis among attributes of the numeric type.
2.48
Third quartile of standard deviation of attributes of the numeric type.
38.94
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.46
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
4.6
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.
21.5
Mean of means among attributes of the numeric type.
-1.2
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.24
First quartile of standard deviation of attributes of the numeric type.
0.02
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.
2.98
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.85
Number of attributes divided by the number of instances.
0.52
Mean skewness among attributes of the numeric type.
5.25
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

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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