Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4329

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4329

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: CHEMBL4329 (TID: 10008), and it has 189 rows and 64 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.

66 features

pXC50 (target)numeric160 unique values
0 missing
molecule_id (row identifier)nominal189 unique values
0 missing
D.Dtr11numeric65 unique values
0 missing
D.Dtr08numeric73 unique values
0 missing
SpMax7_Bh.s.numeric138 unique values
0 missing
P_VSA_MR_7numeric12 unique values
0 missing
ATSC7snumeric176 unique values
0 missing
MSDnumeric145 unique values
0 missing
ATSC8snumeric176 unique values
0 missing
TIC1numeric160 unique values
0 missing
nHetnumeric18 unique values
0 missing
AECCnumeric132 unique values
0 missing
IDEnumeric135 unique values
0 missing
D.Dtr03numeric43 unique values
0 missing
DECCnumeric128 unique values
0 missing
HVcpxnumeric133 unique values
0 missing
ICRnumeric119 unique values
0 missing
IC2numeric150 unique values
0 missing
MATS2vnumeric113 unique values
0 missing
IC3numeric150 unique values
0 missing
Psi_i_snumeric153 unique values
0 missing
CATS2D_05_AAnumeric8 unique values
0 missing
RBNnumeric22 unique values
0 missing
Eig04_EA.dm.numeric25 unique values
0 missing
nCconjnumeric4 unique values
0 missing
ZM1Kupnumeric150 unique values
0 missing
Eig02_AEA.bo.numeric98 unique values
0 missing
nHAccnumeric17 unique values
0 missing
SpMax6_Bh.s.numeric107 unique values
0 missing
C.016numeric4 unique values
0 missing
NdsCHnumeric4 unique values
0 missing
nR.Csnumeric4 unique values
0 missing
SdsCHnumeric56 unique values
0 missing
ON0numeric89 unique values
0 missing
SaasCnumeric171 unique values
0 missing
CENTnumeric147 unique values
0 missing
TIEnumeric176 unique values
0 missing
P_VSA_LogP_2numeric79 unique values
0 missing
CATS2D_08_DAnumeric12 unique values
0 missing
GMTIVnumeric171 unique values
0 missing
SpMin1_Bh.s.numeric73 unique values
0 missing
ECCnumeric122 unique values
0 missing
CATS2D_07_DAnumeric5 unique values
0 missing
IACnumeric138 unique values
0 missing
TIC0numeric138 unique values
0 missing
IC4numeric139 unique values
0 missing
SpMax4_Bh.s.numeric119 unique values
0 missing
Eig09_EA.ri.numeric125 unique values
0 missing
CSInumeric133 unique values
0 missing
PJI2numeric13 unique values
0 missing
Eig09_AEA.ri.numeric128 unique values
0 missing
SpMax8_Bh.s.numeric131 unique values
0 missing
SpMax3_Bh.s.numeric83 unique values
0 missing
S1Knumeric145 unique values
0 missing
GGI10numeric100 unique values
0 missing
SpMax7_Bh.p.numeric115 unique values
0 missing
ATSC7enumeric158 unique values
0 missing
MDDDnumeric147 unique values
0 missing
D.Dtr10numeric109 unique values
0 missing
Chi1_EA.dm.numeric139 unique values
0 missing
SpMAD_EAnumeric103 unique values
0 missing
P_VSA_p_2numeric61 unique values
0 missing
P_VSA_v_2numeric68 unique values
0 missing
SAaccnumeric64 unique values
0 missing
GGI9numeric117 unique values
0 missing
S2Knumeric147 unique values
0 missing

107 properties

189
Number of instances (rows) of the dataset.
66
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.
65
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
54402.89
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
2.02
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
0.35
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.
1.93
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.
-1.08
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
3.95
Maximum skewness among attributes of the numeric type.
0.05
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
6.69
Third quartile of kurtosis among attributes of the numeric type.
-0.16
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
94863.14
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.48
Percentage of numeric attributes.
84.37
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.
1.52
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
4.34
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.
2.57
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
934.73
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.44
First quartile of kurtosis among attributes of the numeric type.
41.28
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
1.56
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.
1.04
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
1.73
Mean skewness among attributes of the numeric type.
0.59
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.
1569.8
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.
3.58
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.
-1.32
Minimum kurtosis among attributes of the numeric type.
5.7
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
19.71
Maximum kurtosis among attributes of the numeric type.
0.05
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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