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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1293312

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1293312

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: CHEMBL1293312 (TID: 103745), and it has 639 rows and 69 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.

71 features

pXC50 (target)numeric457 unique values
0 missing
molecule_id (row identifier)nominal639 unique values
0 missing
AACnumeric374 unique values
0 missing
AECCnumeric494 unique values
0 missing
ALOGPnumeric585 unique values
0 missing
ALOGP2numeric618 unique values
0 missing
AMRnumeric621 unique values
0 missing
AMWnumeric557 unique values
0 missing
ARRnumeric152 unique values
0 missing
ATS1enumeric422 unique values
0 missing
ATS1inumeric422 unique values
0 missing
ATS1mnumeric435 unique values
0 missing
ATS1pnumeric419 unique values
0 missing
ATS1snumeric427 unique values
0 missing
ATS1vnumeric423 unique values
0 missing
ATS2enumeric433 unique values
0 missing
ATS2inumeric454 unique values
0 missing
ATS2mnumeric436 unique values
0 missing
ATS2pnumeric433 unique values
0 missing
ATS2snumeric455 unique values
0 missing
ATS2vnumeric429 unique values
0 missing
ATS3enumeric462 unique values
0 missing
ATS3inumeric479 unique values
0 missing
ATS3mnumeric453 unique values
0 missing
ATS3pnumeric463 unique values
0 missing
ATS3snumeric445 unique values
0 missing
ATS3vnumeric439 unique values
0 missing
ATS4enumeric477 unique values
0 missing
ATS4inumeric475 unique values
0 missing
ATS4mnumeric472 unique values
0 missing
ATS4pnumeric484 unique values
0 missing
ATS4snumeric470 unique values
0 missing
ATS4vnumeric467 unique values
0 missing
ATS5enumeric498 unique values
0 missing
ATS5inumeric492 unique values
0 missing
ATS5mnumeric495 unique values
0 missing
ATS5pnumeric500 unique values
0 missing
ATS5snumeric502 unique values
0 missing
ATS5vnumeric496 unique values
0 missing
ATS6enumeric497 unique values
0 missing
ATS6inumeric517 unique values
0 missing
ATS6mnumeric494 unique values
0 missing
ATS6pnumeric497 unique values
0 missing
ATS6snumeric508 unique values
0 missing
ATS6vnumeric510 unique values
0 missing
ATS7enumeric508 unique values
0 missing
ATS7inumeric533 unique values
0 missing
ATS7mnumeric504 unique values
0 missing
ATS7pnumeric511 unique values
0 missing
ATS7snumeric511 unique values
0 missing
ATS7vnumeric515 unique values
0 missing
ATS8enumeric529 unique values
0 missing
ATS8inumeric517 unique values
0 missing
ATS8mnumeric529 unique values
0 missing
ATS8pnumeric535 unique values
0 missing
ATS8snumeric516 unique values
0 missing
ATS8vnumeric518 unique values
0 missing
ATSC1enumeric257 unique values
0 missing
ATSC1inumeric377 unique values
0 missing
ATSC1mnumeric591 unique values
0 missing
ATSC1pnumeric564 unique values
0 missing
ATSC1snumeric622 unique values
0 missing
ATSC1vnumeric583 unique values
0 missing
ATSC2enumeric405 unique values
0 missing
ATSC2inumeric452 unique values
0 missing
ATSC2mnumeric614 unique values
0 missing
ATSC2pnumeric604 unique values
0 missing
ATSC2snumeric632 unique values
0 missing
ATSC2vnumeric602 unique values
0 missing
ATSC3enumeric429 unique values
0 missing
ATSC3inumeric491 unique values
0 missing

62 properties

639
Number of instances (rows) of the dataset.
71
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.
70
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.
0.11
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.79
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.
-0.3
Mean skewness among attributes of the numeric type.
4.09
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
1.52
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.
-0.49
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.1
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.36
Second quartile (Median) of standard deviation of attributes of the numeric type.
22.24
Maximum kurtosis among attributes of the numeric type.
0.14
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
104.8
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.
1.3
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.
98.59
Percentage of numeric attributes.
5.23
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-2.39
Minimum skewness among attributes of the numeric type.
1.41
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
1.93
Maximum skewness among attributes of the numeric type.
0.08
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.26
Third quartile of skewness among attributes of the numeric type.
27.9
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.
0.5
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.
3.72
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
1.75
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.
6.7
Mean of means among attributes of the numeric type.
-0.7
First quartile of skewness among attributes of the numeric type.
0.63
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.25
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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