Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4852

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4852

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: CHEMBL4852 (TID: 30049), and it has 733 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)numeric80 unique values
0 missing
molecule_id (row identifier)nominal733 unique values
0 missing
CATS2D_08_DPnumeric4 unique values
0 missing
Eig07_EAnumeric458 unique values
0 missing
SM15_AEA.bo.numeric458 unique values
0 missing
Eig07_AEA.ri.numeric514 unique values
0 missing
SpMin3_Bh.v.numeric335 unique values
0 missing
Eig08_EA.bo.numeric490 unique values
0 missing
SpMax5_Bh.m.numeric458 unique values
0 missing
Yindexnumeric386 unique values
0 missing
SpMin3_Bh.p.numeric325 unique values
0 missing
Xindexnumeric250 unique values
0 missing
P_VSA_s_5numeric55 unique values
0 missing
Eig06_EAnumeric467 unique values
0 missing
SM14_AEA.bo.numeric467 unique values
0 missing
DECCnumeric507 unique values
0 missing
Vindexnumeric203 unique values
0 missing
Eig11_AEA.ri.numeric495 unique values
0 missing
Eig07_EA.bo.numeric481 unique values
0 missing
Eig08_EA.ri.numeric485 unique values
0 missing
AMRnumeric698 unique values
0 missing
Eig08_AEA.bo.numeric450 unique values
0 missing
Eig06_AEA.ri.numeric524 unique values
0 missing
Eig08_AEA.ri.numeric488 unique values
0 missing
Eig08_EA.ed.numeric562 unique values
0 missing
SM03_AEA.ri.numeric562 unique values
0 missing
Eig07_EA.ed.numeric578 unique values
0 missing
SM02_AEA.ri.numeric578 unique values
0 missing
CSInumeric485 unique values
0 missing
Eig07_EA.ri.numeric509 unique values
0 missing
Rperimnumeric31 unique values
0 missing
SssNHnumeric482 unique values
0 missing
AECCnumeric534 unique values
0 missing
SpMax8_Bh.m.numeric432 unique values
0 missing
IDEnumeric520 unique values
0 missing
Eig08_EAnumeric463 unique values
0 missing
SM02_AEA.dm.numeric463 unique values
0 missing
SpMax6_Bh.m.numeric459 unique values
0 missing
UNIPnumeric182 unique values
0 missing
RDCHInumeric561 unique values
0 missing
MSDnumeric615 unique values
0 missing
Eig09_AEA.ed.numeric487 unique values
0 missing
Eig10_EA.ed.numeric534 unique values
0 missing
SM05_AEA.ri.numeric534 unique values
0 missing
TRSnumeric31 unique values
0 missing
Eig09_EA.ed.numeric546 unique values
0 missing
SM04_AEA.ri.numeric546 unique values
0 missing
X2solnumeric625 unique values
0 missing
Eig07_AEA.bo.numeric455 unique values
0 missing
Eig08_AEA.ed.numeric509 unique values
0 missing
IC5numeric444 unique values
0 missing
SpMax7_Bh.m.numeric431 unique values
0 missing
ECCnumeric359 unique values
0 missing
GMTInumeric654 unique values
0 missing
Wapnumeric622 unique values
0 missing
X1MulPernumeric664 unique values
0 missing
CATS2D_02_DLnumeric11 unique values
0 missing
Psi_i_1numeric677 unique values
0 missing
IC4numeric451 unique values
0 missing
LLS_01numeric7 unique values
0 missing
SNarnumeric170 unique values
0 missing
Xtnumeric116 unique values
0 missing
Hynumeric365 unique values
0 missing
CATS2D_04_DLnumeric14 unique values
0 missing
ATS2pnumeric484 unique values
0 missing
Eta_betaPnumeric50 unique values
0 missing
TPCnumeric534 unique values
0 missing
SMTInumeric652 unique values
0 missing
Eig12_AEA.bo.numeric469 unique values
0 missing
Eig07_AEA.ed.numeric511 unique values
0 missing
Chi1_EA.ed.numeric624 unique values
0 missing

107 properties

733
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.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
1.26
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Maximum entropy among attributes.
-0.78
Minimum kurtosis among attributes of the numeric type.
3.26
Second quartile (Median) of means among attributes of the numeric type.
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
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
126.3
Maximum kurtosis among attributes of the numeric type.
0.13
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
38137.56
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.11
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.1
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.
0.61
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve 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.
-1.73
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
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
9.86
Maximum skewness among attributes of the numeric type.
0.03
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
2.57
Third quartile of kurtosis among attributes of the numeric type.
0.03
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
86626.28
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.59
Percentage of numeric attributes.
6.77
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.
1.41
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
3.59
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.
0.61
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
865.03
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.3
First quartile of kurtosis among attributes of the numeric type.
2.19
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
1.84
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
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.
-0.66
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
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
0.12
Mean skewness among attributes of the numeric type.
0.35
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
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
1444.58
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
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

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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