Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4225

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4225

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: CHEMBL4225 (TID: 30014), and it has 987 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)numeric123 unique values
0 missing
molecule_id (row identifier)nominal987 unique values
0 missing
SaaNHnumeric246 unique values
0 missing
nPyrrolesnumeric3 unique values
0 missing
NaaNHnumeric3 unique values
0 missing
GMTIVnumeric951 unique values
0 missing
SaaaCnumeric544 unique values
0 missing
NaaaCnumeric7 unique values
0 missing
Eig09_AEA.dm.numeric629 unique values
0 missing
GGI6numeric527 unique values
0 missing
SMTIVnumeric942 unique values
0 missing
XMODnumeric922 unique values
0 missing
X2solnumeric825 unique values
0 missing
JGI4numeric49 unique values
0 missing
CATS2D_07_DAnumeric7 unique values
0 missing
CATS2D_09_LLnumeric24 unique values
0 missing
Chi1_EA.ri.numeric925 unique values
0 missing
SpAD_AEA.ed.numeric865 unique values
0 missing
Cl.090numeric2 unique values
0 missing
ICRnumeric494 unique values
0 missing
D.Dtr06numeric870 unique values
0 missing
Eig11_AEA.dm.numeric605 unique values
0 missing
BIDnumeric145 unique values
0 missing
Dznumeric280 unique values
0 missing
HDcpxnumeric265 unique values
0 missing
IDMnumeric709 unique values
0 missing
SpAD_AEA.dm.numeric921 unique values
0 missing
X2numeric824 unique values
0 missing
ATS6mnumeric687 unique values
0 missing
ATS1mnumeric558 unique values
0 missing
X0solnumeric540 unique values
0 missing
ECCnumeric429 unique values
0 missing
Eig06_AEA.ed.numeric662 unique values
0 missing
X3solnumeric837 unique values
0 missing
DECCnumeric623 unique values
0 missing
Eig14_AEA.ed.numeric600 unique values
0 missing
Psi_e_1numeric857 unique values
0 missing
CSInumeric598 unique values
0 missing
Eig09_EA.ed.numeric707 unique values
0 missing
SM04_AEA.ri.numeric707 unique values
0 missing
Eig10_EA.ri.numeric631 unique values
0 missing
Eig11_AEA.ed.numeric579 unique values
0 missing
SpDiam_EA.ed.numeric665 unique values
0 missing
DBInumeric48 unique values
0 missing
Eig11_EAnumeric563 unique values
0 missing
Eig11_EA.ri.numeric644 unique values
0 missing
SM05_AEA.dm.numeric563 unique values
0 missing
S0Knumeric247 unique values
0 missing
X0numeric391 unique values
0 missing
X1solnumeric753 unique values
0 missing
Eig03_AEA.bo.numeric525 unique values
0 missing
Eig06_AEA.ri.numeric653 unique values
0 missing
Eig06_EA.ri.numeric662 unique values
0 missing
Eig08_AEA.ed.numeric641 unique values
0 missing
SpMax8_Bh.m.numeric544 unique values
0 missing
ATS2vnumeric589 unique values
0 missing
Eig11_AEA.bo.numeric598 unique values
0 missing
AMRnumeric940 unique values
0 missing
Eig03_EAnumeric517 unique values
0 missing
SM11_AEA.bo.numeric517 unique values
0 missing
Eig09_AEA.bo.numeric577 unique values
0 missing
SpDiam_EA.ri.numeric433 unique values
0 missing
SpMax1_Bh.i.numeric245 unique values
0 missing
Eig03_AEA.ri.numeric539 unique values
0 missing
MPC08numeric248 unique values
0 missing
ATS1vnumeric570 unique values
0 missing
Eig08_EA.ri.numeric613 unique values
0 missing
Eta_alphanumeric570 unique values
0 missing
Eta_Cnumeric956 unique values
0 missing
MWC03numeric195 unique values
0 missing
SpMax7_Bh.s.numeric639 unique values
0 missing

107 properties

987
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.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
29747.87
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.08
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
0.07
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.
0.71
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.
-2.68
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
4.6
Maximum skewness among attributes of the numeric type.
0.01
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
3.09
Third quartile of kurtosis among attributes of the numeric type.
0.19
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
19596.71
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.59
Percentage of numeric attributes.
12.85
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
2.31
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.
0.54
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
690.57
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.29
First quartile of kurtosis among attributes of the numeric type.
2.95
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
1.69
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.
-1.02
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
-0.07
Mean skewness among attributes of the numeric type.
0.39
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.
445.64
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.
1.34
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.
-0.79
Minimum kurtosis among attributes of the numeric type.
3.66
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
19.22
Maximum kurtosis among attributes of the numeric type.
0.04
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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