Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741221

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1741221

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: CHEMBL1741221 (TID: 104017), and it has 330 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)numeric224 unique values
0 missing
molecule_id (row identifier)nominal330 unique values
0 missing
ATSC7inumeric289 unique values
0 missing
GMTInumeric320 unique values
0 missing
IDETnumeric324 unique values
0 missing
IDMTnumeric325 unique values
0 missing
LPRSnumeric325 unique values
0 missing
SMTInumeric323 unique values
0 missing
Xunumeric320 unique values
0 missing
MATS1vnumeric125 unique values
0 missing
AACnumeric254 unique values
0 missing
AECCnumeric292 unique values
0 missing
ALOGPnumeric314 unique values
0 missing
ALOGP2numeric326 unique values
0 missing
AMRnumeric328 unique values
0 missing
AMWnumeric314 unique values
0 missing
ARRnumeric119 unique values
0 missing
ATS1enumeric272 unique values
0 missing
ATS1inumeric270 unique values
0 missing
ATS1mnumeric272 unique values
0 missing
ATS1pnumeric272 unique values
0 missing
ATS1snumeric275 unique values
0 missing
ATS1vnumeric271 unique values
0 missing
ATS2enumeric276 unique values
0 missing
ATS2inumeric284 unique values
0 missing
ATS2mnumeric270 unique values
0 missing
ATS2pnumeric282 unique values
0 missing
ATS2snumeric272 unique values
0 missing
ATS2vnumeric271 unique values
0 missing
ATS3enumeric276 unique values
0 missing
ATS3inumeric275 unique values
0 missing
ATS3mnumeric272 unique values
0 missing
ATS3pnumeric276 unique values
0 missing
ATS3snumeric273 unique values
0 missing
ATS3vnumeric275 unique values
0 missing
ATS4enumeric293 unique values
0 missing
ATS4inumeric279 unique values
0 missing
ATS4mnumeric287 unique values
0 missing
ATS4pnumeric281 unique values
0 missing
ATS4snumeric285 unique values
0 missing
ATS4vnumeric281 unique values
0 missing
ATS5enumeric292 unique values
0 missing
ATS5inumeric294 unique values
0 missing
ATS5mnumeric292 unique values
0 missing
ATS5pnumeric295 unique values
0 missing
ATS5snumeric287 unique values
0 missing
ATS5vnumeric295 unique values
0 missing
ATS6enumeric293 unique values
0 missing
ATS6inumeric293 unique values
0 missing
ATS6mnumeric296 unique values
0 missing
ATS6pnumeric289 unique values
0 missing
ATS6snumeric294 unique values
0 missing
ATS6vnumeric294 unique values
0 missing
ATS7enumeric299 unique values
0 missing
ATS7inumeric302 unique values
0 missing
ATS7mnumeric294 unique values
0 missing
ATS7pnumeric285 unique values
0 missing
ATS7snumeric288 unique values
0 missing
ATS7vnumeric294 unique values
0 missing
ATS8enumeric303 unique values
0 missing
ATS8inumeric300 unique values
0 missing
ATS8mnumeric299 unique values
0 missing
ATS8pnumeric286 unique values
0 missing
ATS8snumeric300 unique values
0 missing
ATS8vnumeric293 unique values
0 missing
ATSC1enumeric166 unique values
0 missing
ATSC1inumeric259 unique values
0 missing
ATSC1mnumeric321 unique values
0 missing
ATSC1pnumeric317 unique values
0 missing
ATSC1snumeric324 unique values
0 missing
ATSC1vnumeric320 unique values
0 missing

62 properties

330
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.
0.61
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.22
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
4.38
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.
0.18
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.
400.78
Mean standard deviation of attributes of the numeric type.
-0.04
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.
0.38
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.17
Minimum kurtosis among attributes of the numeric type.
0.02
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
70.97
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
3.33
Third quartile of kurtosis among attributes of the numeric type.
17718.17
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
98.59
Percentage of numeric attributes.
5.6
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
-2.13
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.
The maximum number of distinct values among attributes of the nominal type.
0.04
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.35
Third quartile of skewness among attributes of the numeric type.
6.18
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0.31
First quartile of kurtosis among attributes of the numeric type.
0.57
Third quartile of standard deviation of attributes of the numeric type.
14435.24
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
3.79
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.
4.47
Mean kurtosis among attributes of the numeric type.
-0.39
First quartile of skewness among attributes of the numeric type.
543.14
Mean of means among attributes of the numeric type.
0.26
First quartile of standard deviation of attributes of the numeric type.
0.66
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

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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