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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1250407

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1250407

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: CHEMBL1250407 (TID: 103521), and it has 13 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)numeric8 unique values
0 missing
molecule_id (row identifier)nominal13 unique values
0 missing
AMWnumeric12 unique values
0 missing
C.numeric10 unique values
0 missing
H.numeric10 unique values
0 missing
Menumeric8 unique values
0 missing
Minumeric8 unique values
0 missing
Mpnumeric11 unique values
0 missing
Mvnumeric11 unique values
0 missing
MWnumeric12 unique values
0 missing
N.numeric9 unique values
0 missing
nABnumeric1 unique values
0 missing
nATnumeric9 unique values
0 missing
nBnumeric1 unique values
0 missing
nBMnumeric2 unique values
0 missing
nBOnumeric4 unique values
0 missing
nBRnumeric1 unique values
0 missing
nBTnumeric9 unique values
0 missing
nCnumeric4 unique values
0 missing
nCLnumeric3 unique values
0 missing
nCspnumeric2 unique values
0 missing
nCsp2numeric3 unique values
0 missing
nCsp3numeric5 unique values
0 missing
nDBnumeric2 unique values
0 missing
nFnumeric2 unique values
0 missing
nHnumeric7 unique values
0 missing
nHetnumeric3 unique values
0 missing
nHMnumeric3 unique values
0 missing
nInumeric1 unique values
0 missing
nNnumeric2 unique values
0 missing
nOnumeric3 unique values
0 missing
nPnumeric1 unique values
0 missing
nSnumeric1 unique values
0 missing
nSKnumeric4 unique values
0 missing
nTBnumeric2 unique values
0 missing
nXnumeric3 unique values
0 missing
O.numeric10 unique values
0 missing
RBFnumeric11 unique values
0 missing
RBNnumeric4 unique values
0 missing
SCBOnumeric5 unique values
0 missing
Senumeric12 unique values
0 missing
Sinumeric12 unique values
0 missing
Spnumeric12 unique values
0 missing
Svnumeric12 unique values
0 missing
X.numeric6 unique values
0 missing

62 properties

13
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.
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.
3.46
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.08
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.
0.69
Mean skewness among attributes of the numeric type.
6.74
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1.32
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.
0.48
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.61
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.75
Second quartile (Median) of standard deviation of attributes of the numeric type.
13
Maximum 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.
506.9
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.
0.97
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.
97.78
Percentage of numeric attributes.
35.04
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.18
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.
3.61
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.23
Third quartile of skewness among attributes of the numeric type.
19.46
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.49
First quartile of kurtosis among attributes of the numeric type.
1.1
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.
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.
1.46
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.
27.68
Mean of means among attributes of the numeric type.
-0.46
First quartile of skewness among attributes of the numeric type.
0.32
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.08
First quartile of standard deviation of attributes of the numeric type.

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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