DEVELOPMENT... OpenML
Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1825

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1825

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by unknown
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL1825 (TID: 185), and it has 443 rows and 67 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.

69 features

pXC50 (target)numeric216 unique values
0 missing
SM04_AEA.ri.numeric308 unique values
0 missing
Eig05_EA.ri.numeric339 unique values
0 missing
Eig09_EA.ed.numeric308 unique values
0 missing
Eig09_AEA.ri.numeric303 unique values
0 missing
ATSC7inumeric368 unique values
0 missing
Eig09_AEA.ed.numeric284 unique values
0 missing
X4numeric363 unique values
0 missing
ATS3vnumeric335 unique values
0 missing
SpMax1_Bh.i.numeric170 unique values
0 missing
SpMax2_Bh.p.numeric181 unique values
0 missing
ATS5inumeric361 unique values
0 missing
SssNHnumeric213 unique values
0 missing
GNarnumeric160 unique values
0 missing
ATSC4vnumeric434 unique values
0 missing
ATSC2inumeric333 unique values
0 missing
Senumeric379 unique values
0 missing
Eig02_EA.ri.numeric274 unique values
0 missing
TIC1numeric386 unique values
0 missing
Eig04_AEA.bo.numeric277 unique values
0 missing
SpMaxA_EA.bo.numeric112 unique values
0 missing
ATSC5inumeric379 unique values
0 missing
C.005numeric5 unique values
0 missing
TIC3numeric360 unique values
0 missing
PDInumeric151 unique values
0 missing
ATSC4mnumeric438 unique values
0 missing
Eig07_AEA.ed.numeric310 unique values
0 missing
Ramnumeric14 unique values
0 missing
Eig09_EA.ri.numeric308 unique values
0 missing
Eta_Cnumeric437 unique values
0 missing
SpMin1_Bh.s.numeric172 unique values
0 missing
SAtotnumeric405 unique values
0 missing
X5solnumeric380 unique values
0 missing
ATS3inumeric326 unique values
0 missing
ATS6pnumeric373 unique values
0 missing
MCDnumeric123 unique values
0 missing
RBFnumeric121 unique values
0 missing
SM12_AEA.bo.numeric294 unique values
0 missing
Eig04_EAnumeric294 unique values
0 missing
TPCnumeric308 unique values
0 missing
ATS4enumeric364 unique values
0 missing
SM13_AEA.dm.numeric328 unique values
0 missing
Eig04_EA.ed.numeric328 unique values
0 missing
ATS3pnumeric348 unique values
0 missing
RCInumeric22 unique values
0 missing
ATS4inumeric351 unique values
0 missing
SpMax2_Bh.v.numeric180 unique values
0 missing
Eig04_EA.ri.numeric333 unique values
0 missing
ATS4pnumeric350 unique values
0 missing
Eig04_AEA.ri.numeric327 unique values
0 missing
MATS1vnumeric157 unique values
0 missing
LOCnumeric239 unique values
0 missing
ATS5pnumeric354 unique values
0 missing
SM05_AEA.ri.numeric289 unique values
0 missing
Eig10_EA.ed.numeric289 unique values
0 missing
ATS3enumeric334 unique values
0 missing
ATSC4pnumeric434 unique values
0 missing
ATS4vnumeric346 unique values
0 missing
MATS3vnumeric269 unique values
0 missing
ATSC3inumeric358 unique values
0 missing
nArORnumeric4 unique values
0 missing
molecule_id (row identifier)nominal443 unique values
0 missing
Wapnumeric352 unique values
0 missing
SM14_AEA.ri.numeric297 unique values
0 missing
Eig04_EA.bo.numeric297 unique values
0 missing
Eig10_AEA.ed.numeric274 unique values
0 missing
ATSC4inumeric373 unique values
0 missing
ATSC6inumeric395 unique values
0 missing
RFDnumeric21 unique values
0 missing

62 properties

443
Number of instances (rows) of the dataset.
69
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.
68
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.
98.55
Percentage of numeric attributes.
1.45
Percentage of nominal attributes.
First quartile of entropy among attributes.
-0.01
First quartile of kurtosis among attributes of the numeric type.
1.28
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.39
First quartile of skewness among attributes of the numeric type.
0.23
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
3.31
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.
-0.07
Second quartile (Median) of skewness among attributes of the numeric type.
0.35
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
0.89
Third quartile of kurtosis among attributes of the numeric type.
4.9
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.54
Third quartile of skewness among attributes of the numeric type.
1.1
Third quartile of standard deviation of attributes of the numeric type.
0.4
Average class difference between consecutive instances.
270.24
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.16
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.
70.48
Maximum kurtosis among attributes of the numeric type.
17250.75
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.
3.1
Maximum skewness among attributes of the numeric type.
17298.05
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
1.67
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.
-0.01
Mean skewness among attributes of the numeric type.
257.89
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-0.52
Minimum kurtosis among attributes of the numeric type.
-0.04
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.
-6.43
Minimum skewness among attributes of the numeric type.
0.03
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
Define a new task