DEVELOPMENT... OpenML
Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2717

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2717

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 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: CHEMBL2717 (TID: 12448), and it has 121 rows and 63 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.

65 features

pXC50 (target)numeric88 unique values
0 missing
Eig14_EAnumeric80 unique values
0 missing
ATS6vnumeric105 unique values
0 missing
Eig14_AEA.ri.numeric96 unique values
0 missing
Eig13_EA.ri.numeric87 unique values
0 missing
Eig13_EAnumeric74 unique values
0 missing
Eig13_AEA.ri.numeric90 unique values
0 missing
Eig10_AEA.ri.numeric87 unique values
0 missing
Eig08_EA.ri.numeric100 unique values
0 missing
ATSC7pnumeric118 unique values
0 missing
ATSC6vnumeric119 unique values
0 missing
ATSC6pnumeric117 unique values
0 missing
ATSC5inumeric114 unique values
0 missing
ATSC4pnumeric117 unique values
0 missing
ATSC3vnumeric114 unique values
0 missing
ATSC3pnumeric112 unique values
0 missing
C.008numeric4 unique values
0 missing
Eig14_EA.ri.numeric99 unique values
0 missing
IC5numeric85 unique values
0 missing
Psi_i_1numeric112 unique values
0 missing
SM02_EA.ri.numeric96 unique values
0 missing
SM07_AEA.dm.numeric74 unique values
0 missing
SM08_AEA.dm.numeric80 unique values
0 missing
SNarnumeric62 unique values
0 missing
SpAD_EA.ri.numeric117 unique values
0 missing
SpMaxA_AEA.dm.numeric43 unique values
0 missing
X2solnumeric91 unique values
0 missing
X3solnumeric90 unique values
0 missing
X3vnumeric117 unique values
0 missing
Xtnumeric51 unique values
0 missing
MAXDPnumeric112 unique values
0 missing
ATSC3inumeric114 unique values
0 missing
X2vnumeric117 unique values
0 missing
ATSC5vnumeric118 unique values
0 missing
Eig04_EA.dm.numeric17 unique values
0 missing
SaaNHnumeric31 unique values
0 missing
SpMAD_EA.ri.numeric80 unique values
0 missing
ATS4enumeric107 unique values
0 missing
ATS5vnumeric106 unique values
0 missing
D.Dtr09numeric57 unique values
0 missing
Eig03_EA.dm.numeric17 unique values
0 missing
nRCONR2numeric4 unique values
0 missing
Eig11_AEA.dm.numeric71 unique values
0 missing
ATS2vnumeric100 unique values
0 missing
ATS3enumeric99 unique values
0 missing
ATS5pnumeric106 unique values
0 missing
ATS6enumeric114 unique values
0 missing
ATS6inumeric107 unique values
0 missing
ATSC5pnumeric117 unique values
0 missing
molecule_id (row identifier)nominal121 unique values
0 missing
ATSC6mnumeric119 unique values
0 missing
Eig08_AEA.ri.numeric98 unique values
0 missing
Eig14_EA.ed.numeric85 unique values
0 missing
SM09_AEA.ri.numeric85 unique values
0 missing
TIC4numeric85 unique values
0 missing
TIC5numeric85 unique values
0 missing
X5vnumeric112 unique values
0 missing
nCICnumeric7 unique values
0 missing
ATSC4vnumeric119 unique values
0 missing
SsssNnumeric58 unique values
0 missing
CATS2D_07_ALnumeric17 unique values
0 missing
GATS6snumeric104 unique values
0 missing
GNarnumeric70 unique values
0 missing
HNarnumeric62 unique values
0 missing
X0Anumeric47 unique values
0 missing

62 properties

121
Number of instances (rows) of the dataset.
65
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.
64
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.
98.46
Percentage of numeric attributes.
1.54
Percentage of nominal attributes.
First quartile of entropy among attributes.
-0.87
First quartile of kurtosis among attributes of the numeric type.
1.03
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.
0.31
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
-0.67
Second quartile (Median) of kurtosis among attributes of the numeric type.
4.17
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.
0.15
Second quartile (Median) of skewness among attributes of the numeric type.
0.66
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
-0.27
Third quartile of kurtosis among attributes of the numeric type.
11.77
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.58
Third quartile of skewness among attributes of the numeric type.
3.53
Third quartile of standard deviation of attributes of the numeric type.
0.27
Average class difference between consecutive instances.
16.92
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.54
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.
2.05
Maximum kurtosis among attributes of the numeric type.
297.51
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.
1.42
Maximum skewness among attributes of the numeric type.
125.32
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
-0.49
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.
0.14
Mean skewness among attributes of the numeric type.
6.06
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-1.09
Minimum kurtosis among attributes of the numeric type.
0.11
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.
-1.25
Minimum skewness among attributes of the numeric type.
0.02
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