Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL257

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL257

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL257 (TID: 10026), and it has 621 rows and 66 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.

68 features

pXC50 (target)numeric321 unique values
0 missing
molecule_id (row identifier)nominal621 unique values
0 missing
ATSC8pnumeric599 unique values
0 missing
ATS8inumeric414 unique values
0 missing
F.084numeric4 unique values
0 missing
ATSC8vnumeric607 unique values
0 missing
SpMin5_Bh.i.numeric233 unique values
0 missing
P_VSA_MR_5numeric374 unique values
0 missing
ATSC5pnumeric591 unique values
0 missing
CATS2D_07_AAnumeric8 unique values
0 missing
TIC1numeric544 unique values
0 missing
SM03_AEA.bo.numeric311 unique values
0 missing
Eig13_EA.ed.numeric313 unique values
0 missing
SM08_AEA.ri.numeric313 unique values
0 missing
SpAD_EA.bo.numeric514 unique values
0 missing
X4numeric483 unique values
0 missing
IACnumeric456 unique values
0 missing
TIC0numeric456 unique values
0 missing
SpMin5_Bh.s.numeric247 unique values
0 missing
BBInumeric51 unique values
0 missing
MPC02numeric51 unique values
0 missing
SM02_EAnumeric51 unique values
0 missing
TIC3numeric522 unique values
0 missing
S2Knumeric496 unique values
0 missing
SNarnumeric142 unique values
0 missing
Xtnumeric70 unique values
0 missing
NssNHnumeric5 unique values
0 missing
SpAD_EA.ed.numeric495 unique values
0 missing
SM02_AEA.ed.numeric178 unique values
0 missing
Eig12_AEA.dm.numeric279 unique values
0 missing
Eta_Cnumeric612 unique values
0 missing
ZM2MulPernumeric584 unique values
0 missing
VvdwZAZnumeric493 unique values
0 missing
SM04_AEA.bo.numeric361 unique values
0 missing
X0solnumeric336 unique values
0 missing
SM03_AEA.ed.numeric342 unique values
0 missing
X3numeric482 unique values
0 missing
SRW06numeric299 unique values
0 missing
SRW08numeric347 unique values
0 missing
ATS3enumeric390 unique values
0 missing
MWC05numeric328 unique values
0 missing
MWC06numeric333 unique values
0 missing
ICRnumeric340 unique values
0 missing
TIC2numeric560 unique values
0 missing
ZM2Pernumeric584 unique values
0 missing
ZM2Vnumeric330 unique values
0 missing
SpMin4_Bh.i.numeric200 unique values
0 missing
Eig10_AEA.ed.numeric314 unique values
0 missing
X5numeric478 unique values
0 missing
SpAD_EA.dm.numeric200 unique values
0 missing
SM02_EA.ed.numeric317 unique values
0 missing
S1Knumeric444 unique values
0 missing
SM04_EA.ri.numeric394 unique values
0 missing
GGI7numeric342 unique values
0 missing
Eig13_AEA.ed.numeric291 unique values
0 missing
ATSC2vnumeric557 unique values
0 missing
Senumeric485 unique values
0 missing
Eig11_AEA.dm.numeric320 unique values
0 missing
SM04_EAnumeric238 unique values
0 missing
ATS6vnumeric411 unique values
0 missing
SpMax6_Bh.m.numeric284 unique values
0 missing
X0vnumeric533 unique values
0 missing
ATS7enumeric433 unique values
0 missing
TIC4numeric484 unique values
0 missing
MDDDnumeric483 unique values
0 missing
VARnumeric226 unique values
0 missing
SRW10numeric351 unique values
0 missing
MPC03numeric66 unique values
0 missing

107 properties

621
Number of instances (rows) of the dataset.
68
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.
67
Number of numeric attributes.
1
Number of nominal attributes.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
996.36
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.19
Second quartile (Median) of skewness among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.11
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.92
Second quartile (Median) of standard deviation of attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
The maximum number of distinct values among attributes of the nominal type.
-1.04
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.56
Maximum skewness among attributes of the numeric type.
0.02
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.3
Third quartile of kurtosis among attributes of the numeric type.
-0.23
Average class difference between consecutive instances.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
215.49
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.53
Percentage of numeric attributes.
54.48
Third quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1.47
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.01
Mean kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.3
Third quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
86.02
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.04
First quartile of kurtosis among attributes of the numeric type.
11.37
Third quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.43
First quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.
-0.65
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.08
Mean skewness among attributes of the numeric type.
0.21
First quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
18.12
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.4
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.09
Minimum kurtosis among attributes of the numeric type.
8.91
Second quartile (Median) of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
10.39
Maximum kurtosis among attributes of the numeric type.
0.17
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

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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