Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3314

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3314

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: CHEMBL3314 (TID: 10081), and it has 248 rows and 68 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.

70 features

pXC50 (target)numeric163 unique values
0 missing
molecule_id (row identifier)nominal248 unique values
0 missing
Eig15_AEA.bo.numeric133 unique values
0 missing
Eig15_EA.bo.numeric140 unique values
0 missing
Eig07_AEA.bo.numeric177 unique values
0 missing
Eig05_EA.bo.numeric169 unique values
0 missing
SM15_AEA.ri.numeric169 unique values
0 missing
Rperimnumeric30 unique values
0 missing
Vindexnumeric124 unique values
0 missing
Xindexnumeric137 unique values
0 missing
Eta_betanumeric114 unique values
0 missing
Eig04_EA.bo.numeric165 unique values
0 missing
SM14_AEA.ri.numeric165 unique values
0 missing
nCICnumeric9 unique values
0 missing
D.Dtr06numeric191 unique values
0 missing
Eig12_AEA.bo.numeric132 unique values
0 missing
SpMax3_Bh.i.numeric135 unique values
0 missing
piPC02numeric112 unique values
0 missing
SM02_EA.bo.numeric112 unique values
0 missing
X5numeric196 unique values
0 missing
TRSnumeric28 unique values
0 missing
SpMax2_Bh.e.numeric95 unique values
0 missing
SpMin3_Bh.i.numeric147 unique values
0 missing
CATS2D_07_ALnumeric31 unique values
0 missing
Eig12_EA.bo.numeric155 unique values
0 missing
SpMax3_Bh.e.numeric148 unique values
0 missing
SpMax2_Bh.i.numeric93 unique values
0 missing
Eig15_EA.ri.numeric161 unique values
0 missing
nR06numeric7 unique values
0 missing
Eig13_AEA.bo.numeric138 unique values
0 missing
Eig07_EA.bo.numeric174 unique values
0 missing
SpMax3_Bh.p.numeric148 unique values
0 missing
Yindexnumeric164 unique values
0 missing
SpMin3_Bh.e.numeric152 unique values
0 missing
piPC03numeric149 unique values
0 missing
Eig15_AEA.ri.numeric144 unique values
0 missing
piPC01numeric67 unique values
0 missing
SCBOnumeric67 unique values
0 missing
Eig15_EAnumeric128 unique values
0 missing
SM09_AEA.dm.numeric128 unique values
0 missing
X5solnumeric208 unique values
0 missing
SpMin3_Bh.p.numeric149 unique values
0 missing
SpAD_EA.bo.numeric200 unique values
0 missing
Eig11_AEA.bo.numeric140 unique values
0 missing
Eig13_AEA.ri.numeric167 unique values
0 missing
Eig13_EAnumeric142 unique values
0 missing
Eig13_EA.ri.numeric174 unique values
0 missing
SM07_AEA.dm.numeric142 unique values
0 missing
SNarnumeric120 unique values
0 missing
Xtnumeric100 unique values
0 missing
Eig14_AEA.bo.numeric130 unique values
0 missing
Eig06_EA.bo.numeric166 unique values
0 missing
IC4numeric188 unique values
0 missing
D.Dtr09numeric33 unique values
0 missing
Eig12_EAnumeric134 unique values
0 missing
SM06_AEA.dm.numeric134 unique values
0 missing
IDDEnumeric149 unique values
0 missing
SM04_AEA.bo.numeric171 unique values
0 missing
Eig13_EA.bo.numeric167 unique values
0 missing
Wapnumeric173 unique values
0 missing
SM02_AEA.bo.numeric140 unique values
0 missing
X3numeric196 unique values
0 missing
MPC05numeric111 unique values
0 missing
TPCnumeric155 unique values
0 missing
SpMaxA_AEA.ri.numeric99 unique values
0 missing
Eig06_AEA.bo.numeric154 unique values
0 missing
Eig13_EA.ed.numeric157 unique values
0 missing
SM08_AEA.ri.numeric157 unique values
0 missing
GGI7numeric161 unique values
0 missing
X1Madnumeric222 unique values
0 missing

107 properties

248
Number of instances (rows) of the dataset.
70
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.
69
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.
1.69
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.
-1.37
Minimum kurtosis among attributes of the numeric type.
3.05
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
29.5
Maximum kurtosis among attributes of the numeric type.
-0.06
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
25108.75
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.16
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.28
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.
0.87
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.
-4.89
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
3.3
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
7.59
Third quartile of kurtosis among attributes of the numeric type.
-0.2
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
35816.33
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.57
Percentage of numeric attributes.
5.28
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.
1.43
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
4.28
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.
0.87
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
374.34
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.28
First quartile of kurtosis among attributes of the numeric type.
1.32
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
0.79
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.
-0.96
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
-0.28
Mean skewness among attributes of the numeric type.
0.37
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.
525.77
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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