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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL6014

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL6014

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 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: CHEMBL6014 (TID: 102391), and it has 516 rows and 68 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.

70 features

pXC50 (target)numeric19 unique values
0 missing
molecule_id (row identifier)nominal516 unique values
0 missing
Chi0_EA.dm.numeric449 unique values
0 missing
nArNHRnumeric3 unique values
0 missing
Chi1_EA.dm.numeric456 unique values
0 missing
CATS2D_04_DDnumeric4 unique values
0 missing
AACnumeric318 unique values
0 missing
AECCnumeric401 unique values
0 missing
ALOGPnumeric474 unique values
0 missing
ALOGP2numeric496 unique values
0 missing
AMRnumeric497 unique values
0 missing
AMWnumeric427 unique values
0 missing
ARRnumeric157 unique values
0 missing
ATS1enumeric372 unique values
0 missing
ATS1inumeric365 unique values
0 missing
ATS1mnumeric363 unique values
0 missing
ATS1pnumeric355 unique values
0 missing
ATS1snumeric376 unique values
0 missing
ATS1vnumeric360 unique values
0 missing
ATS2enumeric388 unique values
0 missing
ATS2inumeric391 unique values
0 missing
ATS2mnumeric377 unique values
0 missing
ATS2pnumeric373 unique values
0 missing
ATS2snumeric410 unique values
0 missing
ATS2vnumeric371 unique values
0 missing
ATS3enumeric388 unique values
0 missing
ATS3inumeric384 unique values
0 missing
ATS3mnumeric393 unique values
0 missing
ATS3pnumeric376 unique values
0 missing
ATS3snumeric406 unique values
0 missing
ATS3vnumeric386 unique values
0 missing
ATS4enumeric416 unique values
0 missing
ATS4inumeric405 unique values
0 missing
ATS4mnumeric406 unique values
0 missing
ATS4pnumeric408 unique values
0 missing
ATS4snumeric405 unique values
0 missing
ATS4vnumeric396 unique values
0 missing
ATS5enumeric411 unique values
0 missing
ATS5inumeric417 unique values
0 missing
ATS5mnumeric420 unique values
0 missing
ATS5pnumeric410 unique values
0 missing
ATS5snumeric420 unique values
0 missing
ATS5vnumeric417 unique values
0 missing
ATS6enumeric436 unique values
0 missing
ATS6inumeric425 unique values
0 missing
ATS6mnumeric415 unique values
0 missing
ATS6pnumeric417 unique values
0 missing
ATS6snumeric419 unique values
0 missing
ATS6vnumeric420 unique values
0 missing
ATS7enumeric435 unique values
0 missing
ATS7inumeric435 unique values
0 missing
ATS7mnumeric431 unique values
0 missing
ATS7pnumeric436 unique values
0 missing
ATS7snumeric442 unique values
0 missing
ATS7vnumeric430 unique values
0 missing
ATS8enumeric456 unique values
0 missing
ATS8inumeric454 unique values
0 missing
ATS8mnumeric425 unique values
0 missing
ATS8pnumeric452 unique values
0 missing
ATS8snumeric442 unique values
0 missing
ATS8vnumeric440 unique values
0 missing
ATSC1enumeric195 unique values
0 missing
ATSC1inumeric349 unique values
0 missing
ATSC1mnumeric479 unique values
0 missing
ATSC1pnumeric463 unique values
0 missing
ATSC1snumeric496 unique values
0 missing
ATSC1vnumeric465 unique values
0 missing
ATSC2enumeric323 unique values
0 missing
ATSC2inumeric404 unique values
0 missing
ATSC2mnumeric485 unique values
0 missing

62 properties

516
Number of instances (rows) of the dataset.
70
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.
69
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.
0.14
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.34
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.
-0.15
Mean skewness among attributes of the numeric type.
4.02
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1.4
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.
-0.33
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.29
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.35
Second quartile (Median) of standard deviation of attributes of the numeric type.
25.41
Maximum kurtosis among attributes of the numeric type.
0.1
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
105.37
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.
1.65
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.
98.57
Percentage of numeric attributes.
5.27
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.45
Minimum skewness among attributes of the numeric type.
1.43
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
3.8
Maximum skewness among attributes of the numeric type.
0.07
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.24
Third quartile of skewness among attributes of the numeric type.
21.97
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.03
First quartile of kurtosis among attributes of the numeric type.
0.56
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.
3.67
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.97
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.
6.46
Mean of means among attributes of the numeric type.
-0.62
First quartile of skewness among attributes of the numeric type.
0.88
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.26
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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