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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3864

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3864

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by unknown
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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: CHEMBL3864 (TID: 11523), and it has 307 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)numeric232 unique values
0 missing
SpAD_EA.ed.numeric279 unique values
0 missing
ATS3snumeric274 unique values
0 missing
ATSC6mnumeric302 unique values
0 missing
ATSC7inumeric278 unique values
0 missing
ATSC6pnumeric299 unique values
0 missing
ATS7pnumeric275 unique values
0 missing
ATS6vnumeric278 unique values
0 missing
ATS6pnumeric290 unique values
0 missing
ATS5vnumeric277 unique values
0 missing
ATS3vnumeric263 unique values
0 missing
Spnumeric275 unique values
0 missing
P_VSA_i_3numeric261 unique values
0 missing
CIC0numeric257 unique values
0 missing
ATS4mnumeric271 unique values
0 missing
ATSC5mnumeric301 unique values
0 missing
ATS3mnumeric252 unique values
0 missing
ATSC2pnumeric282 unique values
0 missing
ATS6enumeric284 unique values
0 missing
ATS1vnumeric241 unique values
0 missing
SAtotnumeric284 unique values
0 missing
ZM1numeric91 unique values
0 missing
SM02_EA.ri.numeric249 unique values
0 missing
MWC02numeric91 unique values
0 missing
Sinumeric279 unique values
0 missing
nBTnumeric76 unique values
0 missing
nATnumeric74 unique values
0 missing
ISIZnumeric74 unique values
0 missing
SRW04numeric115 unique values
0 missing
ATS7snumeric287 unique values
0 missing
ATS3pnumeric258 unique values
0 missing
X2numeric276 unique values
0 missing
SM02_EAnumeric65 unique values
0 missing
MPC02numeric65 unique values
0 missing
BBInumeric65 unique values
0 missing
ATSC7mnumeric301 unique values
0 missing
ATSC8mnumeric295 unique values
0 missing
ATS7inumeric281 unique values
0 missing
ATS4inumeric266 unique values
0 missing
ATS4enumeric269 unique values
0 missing
ATSC6vnumeric302 unique values
0 missing
ATS6inumeric272 unique values
0 missing
ATS2mnumeric244 unique values
0 missing
ATS7enumeric287 unique values
0 missing
ATSC1pnumeric280 unique values
0 missing
ATSC7pnumeric301 unique values
0 missing
ATS8vnumeric275 unique values
0 missing
TIC5numeric261 unique values
0 missing
TIC4numeric263 unique values
0 missing
TIC3numeric285 unique values
0 missing
ATS8enumeric286 unique values
0 missing
Eta_Cnumeric299 unique values
0 missing
ATSC4mnumeric302 unique values
0 missing
GGI10numeric163 unique values
0 missing
ATS8inumeric275 unique values
0 missing
TIC2numeric292 unique values
0 missing
ATSC3mnumeric293 unique values
0 missing
Eig06_EA.ri.numeric257 unique values
0 missing
ATSC8vnumeric297 unique values
0 missing
ATSC8pnumeric294 unique values
0 missing
ATSC8inumeric273 unique values
0 missing
ATSC2mnumeric283 unique values
0 missing
ATS8pnumeric273 unique values
0 missing
molecule_id (row identifier)nominal307 unique values
0 missing
ATS7vnumeric273 unique values
0 missing
ATS3inumeric259 unique values
0 missing
ATS3enumeric266 unique values
0 missing
ATS2inumeric256 unique values
0 missing
ATS2enumeric250 unique values
0 missing
ATS1pnumeric250 unique values
0 missing
ATSC7vnumeric299 unique values
0 missing

62 properties

307
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
98.59
Percentage of numeric attributes.
1.41
Percentage of nominal attributes.
First quartile of entropy among attributes.
1.27
First quartile of kurtosis among attributes of the numeric type.
4.07
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.1
First quartile of skewness among attributes of the numeric type.
0.46
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
5.17
Second quartile (Median) of kurtosis among attributes of the numeric type.
5
Second quartile (Median) of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.49
Second quartile (Median) of skewness among attributes of the numeric type.
0.82
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
7.81
Third quartile of kurtosis among attributes of the numeric type.
29.69
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
2.15
Third quartile of skewness among attributes of the numeric type.
19.42
Third quartile of standard deviation of attributes of the numeric type.
0.42
Average class difference between consecutive instances.
45.97
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.23
Number of attributes divided by the number of instances.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
31.07
Maximum kurtosis among attributes of the numeric type.
534.22
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
4.08
Maximum skewness among attributes of the numeric type.
206.47
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
5.65
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
Average mutual information between the nominal attributes and the target attribute.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Average number of distinct values among the attributes of the nominal type.
0.88
Mean skewness among attributes of the numeric type.
21.52
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
0.71
Minimum kurtosis among attributes of the numeric type.
0.19
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-2.63
Minimum skewness among attributes of the numeric type.
0.21
Minimum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.

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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