DEVELOPMENT... OpenML
Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2971

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2971

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: CHEMBL2971 (TID: 10938), and it has 1862 rows and 70 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.

72 features

pXC50 (target)numeric572 unique values
0 missing
nBMnumeric32 unique values
0 missing
piPC10numeric1138 unique values
0 missing
SpMax3_Bh.v.numeric597 unique values
0 missing
IC5numeric790 unique values
0 missing
ATSC6vnumeric1739 unique values
0 missing
SpMin3_Bh.s.numeric591 unique values
0 missing
H.047numeric34 unique values
0 missing
Mpnumeric180 unique values
0 missing
SpMin7_Bh.m.numeric684 unique values
0 missing
DLS_04numeric9 unique values
0 missing
MATS1mnumeric221 unique values
0 missing
nCsp3numeric18 unique values
0 missing
nNnumeric13 unique values
0 missing
SpMin3_Bh.m.numeric510 unique values
0 missing
nATnumeric72 unique values
0 missing
ISIZnumeric72 unique values
0 missing
piPC03numeric706 unique values
0 missing
nHetnumeric16 unique values
0 missing
ATS4inumeric1019 unique values
0 missing
NaaNnumeric7 unique values
0 missing
N.075numeric7 unique values
0 missing
SpMin7_Bh.p.numeric700 unique values
0 missing
Eig08_AEA.dm.numeric959 unique values
0 missing
ATSC2mnumeric1641 unique values
0 missing
piPC07numeric1037 unique values
0 missing
Mvnumeric184 unique values
0 missing
P_VSA_e_3numeric460 unique values
0 missing
Ucnumeric32 unique values
0 missing
Eig03_EA.ri.numeric723 unique values
0 missing
P_VSA_i_4numeric621 unique values
0 missing
D.Dtr09numeric895 unique values
0 missing
SpMin8_Bh.m.numeric691 unique values
0 missing
Eig03_AEA.ri.numeric733 unique values
0 missing
NRSnumeric7 unique values
0 missing
SpMax3_Bh.p.numeric611 unique values
0 missing
MATS1vnumeric210 unique values
0 missing
SpMin4_Bh.v.numeric605 unique values
0 missing
P_VSA_m_2numeric1644 unique values
0 missing
SpMin3_Bh.e.numeric546 unique values
0 missing
TIC2numeric1567 unique values
0 missing
ATSC1inumeric720 unique values
0 missing
Eta_betaS_Anumeric147 unique values
0 missing
GATS1pnumeric619 unique values
0 missing
IC2numeric911 unique values
0 missing
Chi0_EA.dm.numeric1419 unique values
0 missing
MATS1inumeric572 unique values
0 missing
Chi1_EA.dm.numeric1488 unique values
0 missing
n124.Triazinesnumeric2 unique values
0 missing
CATS2D_07_AAnumeric10 unique values
0 missing
C.032numeric3 unique values
0 missing
MATS1pnumeric364 unique values
0 missing
SaaNnumeric1397 unique values
0 missing
nArNHRnumeric3 unique values
0 missing
Minumeric85 unique values
0 missing
IC3numeric848 unique values
0 missing
SssCH2numeric1094 unique values
0 missing
C.006numeric11 unique values
0 missing
GATS1vnumeric459 unique values
0 missing
MPC08numeric283 unique values
0 missing
NssCH2numeric14 unique values
0 missing
SpMin3_Bh.v.numeric475 unique values
0 missing
C.numeric165 unique values
0 missing
molecule_id (row identifier)nominal1862 unique values
0 missing
SsssNnumeric585 unique values
0 missing
SpMaxA_AEA.dm.numeric179 unique values
0 missing
SpMin4_Bh.e.numeric676 unique values
0 missing
SpMin3_Bh.i.numeric572 unique values
0 missing
nCICnumeric10 unique values
0 missing
SpMin4_Bh.p.numeric595 unique values
0 missing
TIC3numeric1262 unique values
0 missing
N.073numeric4 unique values
0 missing

62 properties

1862
Number of instances (rows) of the dataset.
72
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.
71
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.
98.61
Percentage of numeric attributes.
1.39
Percentage of nominal attributes.
First quartile of entropy among attributes.
0.01
First quartile of kurtosis among attributes of the numeric type.
1.08
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
First quartile of skewness among attributes of the numeric type.
0.18
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
1.19
Second quartile (Median) of kurtosis among attributes of the numeric type.
2.53
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.
0.25
Second quartile (Median) of skewness among attributes of the numeric type.
0.47
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
2.97
Third quartile of kurtosis among attributes of the numeric type.
7.43
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.67
Third quartile of skewness among attributes of the numeric type.
2.64
Third quartile of standard deviation of attributes of the numeric type.
0.24
Average class difference between consecutive instances.
20.72
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.04
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.
21.42
Maximum kurtosis among attributes of the numeric type.
264.11
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.
4.42
Maximum skewness among attributes of the numeric type.
89.3
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
2.46
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.
0.03
Mean skewness among attributes of the numeric type.
7.38
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-0.9
Minimum kurtosis among attributes of the numeric type.
-0.1
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.
-3.16
Minimum skewness among attributes of the numeric type.
0.01
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

A PHP Error was encountered

Severity: Core Warning

Message: Module 'mysqli' already loaded

Filename: Unknown

Line Number: 0

Backtrace: