Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3160

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3160

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: CHEMBL3160 (TID: 10045), and it has 470 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)numeric316 unique values
0 missing
molecule_id (row identifier)nominal470 unique values
0 missing
nHetnumeric20 unique values
0 missing
SM05_EA.bo.numeric193 unique values
0 missing
nCsnumeric13 unique values
0 missing
nCsp3numeric16 unique values
0 missing
ATSC6inumeric375 unique values
0 missing
C.002numeric10 unique values
0 missing
ATSC1mnumeric359 unique values
0 missing
Eig08_AEA.bo.numeric153 unique values
0 missing
ATSC7pnumeric429 unique values
0 missing
SpMax8_Bh.p.numeric240 unique values
0 missing
ATSC8inumeric375 unique values
0 missing
ATSC5inumeric377 unique values
0 missing
ATS6vnumeric331 unique values
0 missing
Eig14_AEA.dm.numeric214 unique values
0 missing
TPSA.NO.numeric134 unique values
0 missing
ATS7pnumeric347 unique values
0 missing
SAaccnumeric169 unique values
0 missing
ATSC4inumeric380 unique values
0 missing
ATSC5pnumeric422 unique values
0 missing
Eig12_AEA.bo.numeric187 unique values
0 missing
ATSC1inumeric281 unique values
0 missing
CATS2D_08_ALnumeric22 unique values
0 missing
ZM2Kupnumeric404 unique values
0 missing
Eig12_EA.bo.numeric181 unique values
0 missing
ATSC4pnumeric426 unique values
0 missing
ATSC8mnumeric433 unique values
0 missing
Eig11_EA.ed.numeric174 unique values
0 missing
SM06_AEA.ri.numeric174 unique values
0 missing
ATS8inumeric353 unique values
0 missing
P_VSA_MR_2numeric85 unique values
0 missing
Eig15_AEA.ed.numeric200 unique values
0 missing
X0vnumeric375 unique values
0 missing
Eig13_EA.ri.numeric260 unique values
0 missing
ATS8pnumeric350 unique values
0 missing
ATSC4vnumeric431 unique values
0 missing
Eig08_AEA.dm.numeric245 unique values
0 missing
Eig09_AEA.ed.numeric155 unique values
0 missing
GGI9numeric174 unique values
0 missing
SpMin2_Bh.s.numeric129 unique values
0 missing
Eig09_EA.ed.numeric189 unique values
0 missing
SM04_AEA.ri.numeric189 unique values
0 missing
ATSC8pnumeric420 unique values
0 missing
SM08_EA.bo.numeric231 unique values
0 missing
Psi_i_1numeric389 unique values
0 missing
ZM2Vnumeric227 unique values
0 missing
Eig12_EA.ri.numeric221 unique values
0 missing
SpAD_AEA.ed.numeric264 unique values
0 missing
ATS2vnumeric293 unique values
0 missing
Eig15_EA.ed.numeric200 unique values
0 missing
SM10_AEA.ri.numeric200 unique values
0 missing
Eig12_EAnumeric172 unique values
0 missing
SM06_AEA.dm.numeric172 unique values
0 missing
ATS2pnumeric289 unique values
0 missing
MWC02numeric79 unique values
0 missing
ZM1numeric79 unique values
0 missing
X1solnumeric228 unique values
0 missing
ATS7enumeric329 unique values
0 missing
ATS1pnumeric261 unique values
0 missing
Eig12_AEA.ri.numeric228 unique values
0 missing
Eig06_AEA.ed.numeric126 unique values
0 missing
SpMax8_Bh.i.numeric206 unique values
0 missing
Spnumeric321 unique values
0 missing
SpMin7_Bh.s.numeric205 unique values
0 missing
SM03_EA.bo.numeric79 unique values
0 missing
ZM2Pernumeric416 unique values
0 missing
SpMin8_Bh.s.numeric187 unique values
0 missing
ATSC7enumeric385 unique values
0 missing
SpMin7_Bh.m.numeric238 unique values
0 missing

107 properties

470
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.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
863.11
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.75
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
0.15
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.
0.53
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.
-6.59
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
1.67
Maximum skewness among attributes of the numeric type.
0.09
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
9.64
Third quartile of kurtosis among attributes of the numeric type.
-0.12
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
157.67
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.57
Percentage of numeric attributes.
12.3
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
9.88
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.
0.47
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
47.5
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.89
First quartile of kurtosis among attributes of the numeric type.
3.24
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
1.81
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.
-2.17
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
-0.97
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.
10.58
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
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.
5.15
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.
-0.8
Minimum kurtosis among attributes of the numeric type.
4.12
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
70.85
Maximum kurtosis among attributes of the numeric type.
0.35
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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