Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by Noureddin Sadawi
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL4501 (TID: 12944), and it has 887 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)numeric163 unique values
0 missing
molecule_id (row identifier)nominal887 unique values
0 missing
CATS2D_06_PLnumeric9 unique values
0 missing
SsNH2numeric297 unique values
0 missing
SaaaCnumeric503 unique values
0 missing
nArNH2numeric3 unique values
0 missing
CATS2D_02_APnumeric7 unique values
0 missing
N.069numeric3 unique values
0 missing
CATS2D_05_PLnumeric10 unique values
0 missing
SpMax1_Bh.p.numeric273 unique values
0 missing
CATS2D_00_DDnumeric8 unique values
0 missing
CATS2D_00_DPnumeric8 unique values
0 missing
CATS2D_00_PPnumeric8 unique values
0 missing
NsNH2numeric8 unique values
0 missing
CATS2D_08_DPnumeric8 unique values
0 missing
CATS2D_04_PLnumeric10 unique values
0 missing
Eig09_AEA.ri.numeric568 unique values
0 missing
SpMax7_Bh.m.numeric496 unique values
0 missing
SpMax1_Bh.v.numeric259 unique values
0 missing
Eig08_AEA.bo.numeric536 unique values
0 missing
Eig01_EA.bo.numeric410 unique values
0 missing
SM11_AEA.ri.numeric410 unique values
0 missing
SpDiam_EA.bo.numeric411 unique values
0 missing
SpMax_EA.bo.numeric410 unique values
0 missing
C.025numeric9 unique values
0 missing
CATS2D_03_PLnumeric6 unique values
0 missing
CATS2D_03_APnumeric5 unique values
0 missing
SM15_EA.bo.numeric657 unique values
0 missing
Eig09_EA.ed.numeric648 unique values
0 missing
SM04_AEA.ri.numeric648 unique values
0 missing
ICRnumeric481 unique values
0 missing
SpMax8_Bh.p.numeric464 unique values
0 missing
Hynumeric428 unique values
0 missing
Eig09_EAnumeric526 unique values
0 missing
SM03_AEA.dm.numeric526 unique values
0 missing
Eig08_AEA.ri.numeric572 unique values
0 missing
SM14_EA.bo.numeric660 unique values
0 missing
CATS2D_02_PLnumeric6 unique values
0 missing
ZM1Madnumeric833 unique values
0 missing
CATS2D_08_DDnumeric9 unique values
0 missing
CATS2D_06_DLnumeric18 unique values
0 missing
ATS2mnumeric571 unique values
0 missing
SM13_EA.bo.numeric646 unique values
0 missing
Eig09_AEA.ed.numeric576 unique values
0 missing
GATS1snumeric405 unique values
0 missing
CATS2D_05_DLnumeric21 unique values
0 missing
SpMax7_Bh.i.numeric476 unique values
0 missing
H.050numeric14 unique values
0 missing
nHDonnumeric14 unique values
0 missing
SpMax2_Bh.i.numeric274 unique values
0 missing
IDEnumeric595 unique values
0 missing
Eig08_EAnumeric528 unique values
0 missing
SM02_AEA.dm.numeric528 unique values
0 missing
Yindexnumeric441 unique values
0 missing
Eig08_EA.ri.numeric560 unique values
0 missing
SpMax6_Bh.m.numeric527 unique values
0 missing
SpMax8_Bh.v.numeric476 unique values
0 missing
Eig11_EA.bo.numeric563 unique values
0 missing
X3vnumeric796 unique values
0 missing
MWnumeric775 unique values
0 missing
Eig08_EA.ed.numeric660 unique values
0 missing
SM03_AEA.ri.numeric660 unique values
0 missing
ATS1mnumeric547 unique values
0 missing
SpMax5_Bh.m.numeric531 unique values
0 missing
MSDnumeric734 unique values
0 missing
SpMax8_Bh.m.numeric511 unique values
0 missing
AECCnumeric625 unique values
0 missing
Eig07_AEA.bo.numeric538 unique values
0 missing
Eig06_AEA.ed.numeric601 unique values
0 missing
DECCnumeric597 unique values
0 missing
Chi1_EA.dm.numeric756 unique values
0 missing

107 properties

887
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
392.75
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.25
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
0.08
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.
0.66
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.
-1.52
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
10.73
Maximum skewness among attributes of the numeric type.
0.07
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
28.04
Third quartile of kurtosis among attributes of the numeric type.
0.22
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
126.77
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
98.59
Percentage of numeric attributes.
3.99
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
20.07
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.
3.47
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
11.8
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.07
First quartile of kurtosis among attributes of the numeric type.
1.47
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
0.85
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.
-0.74
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
1.69
Mean skewness among attributes of the numeric type.
0.32
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.
3.77
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
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.
3.21
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.
-0.39
Minimum kurtosis among attributes of the numeric type.
2.82
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
144.27
Maximum kurtosis among attributes of the numeric type.
0.2
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
Define a new task