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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by unknown
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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: 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
Yindexnumeric441 unique values
0 missing
CATS2D_02_PLnumeric6 unique values
0 missing
SM02_AEA.dm.numeric528 unique values
0 missing
Eig08_EAnumeric528 unique values
0 missing
IDEnumeric595 unique values
0 missing
SpMax2_Bh.i.numeric274 unique values
0 missing
nHDonnumeric14 unique values
0 missing
H.050numeric14 unique values
0 missing
SpMax7_Bh.i.numeric476 unique values
0 missing
CATS2D_05_DLnumeric21 unique values
0 missing
GATS1snumeric405 unique values
0 missing
Eig09_AEA.ed.numeric576 unique values
0 missing
SM13_EA.bo.numeric646 unique values
0 missing
ATS2mnumeric571 unique values
0 missing
CATS2D_06_DLnumeric18 unique values
0 missing
CATS2D_08_DDnumeric9 unique values
0 missing
ZM1Madnumeric833 unique values
0 missing
SM14_EA.bo.numeric660 unique values
0 missing
ATS1mnumeric547 unique values
0 missing
Chi1_EA.dm.numeric756 unique values
0 missing
DECCnumeric597 unique values
0 missing
Eig06_AEA.ed.numeric601 unique values
0 missing
Eig07_AEA.bo.numeric538 unique values
0 missing
AECCnumeric625 unique values
0 missing
SpMax8_Bh.m.numeric511 unique values
0 missing
MSDnumeric734 unique values
0 missing
SpMax5_Bh.m.numeric531 unique values
0 missing
Eig08_EA.ri.numeric560 unique values
0 missing
SM03_AEA.ri.numeric660 unique values
0 missing
Eig08_EA.ed.numeric660 unique values
0 missing
MWnumeric775 unique values
0 missing
X3vnumeric796 unique values
0 missing
Eig11_EA.bo.numeric563 unique values
0 missing
SpMax8_Bh.v.numeric476 unique values
0 missing
SpMax6_Bh.m.numeric527 unique values
0 missing
CATS2D_00_DDnumeric8 unique values
0 missing
SpMax1_Bh.v.numeric259 unique values
0 missing
SpMax7_Bh.m.numeric496 unique values
0 missing
Eig09_AEA.ri.numeric568 unique values
0 missing
CATS2D_04_PLnumeric10 unique values
0 missing
CATS2D_08_DPnumeric8 unique values
0 missing
NsNH2numeric8 unique values
0 missing
CATS2D_00_PPnumeric8 unique values
0 missing
CATS2D_00_DPnumeric8 unique values
0 missing
Eig08_AEA.bo.numeric536 unique values
0 missing
SpMax1_Bh.p.numeric273 unique values
0 missing
CATS2D_05_PLnumeric10 unique values
0 missing
N.069numeric3 unique values
0 missing
CATS2D_02_APnumeric7 unique values
0 missing
nArNH2numeric3 unique values
0 missing
SaaaCnumeric503 unique values
0 missing
SsNH2numeric297 unique values
0 missing
CATS2D_06_PLnumeric9 unique values
0 missing
SM15_EA.bo.numeric657 unique values
0 missing
Eig08_AEA.ri.numeric572 unique values
0 missing
SM03_AEA.dm.numeric526 unique values
0 missing
Eig09_EAnumeric526 unique values
0 missing
Hynumeric428 unique values
0 missing
SpMax8_Bh.p.numeric464 unique values
0 missing
ICRnumeric481 unique values
0 missing
SM04_AEA.ri.numeric648 unique values
0 missing
Eig09_EA.ed.numeric648 unique values
0 missing
molecule_id (row identifier)nominal887 unique values
0 missing
CATS2D_03_APnumeric5 unique values
0 missing
CATS2D_03_PLnumeric6 unique values
0 missing
C.025numeric9 unique values
0 missing
SpMax_EA.bo.numeric410 unique values
0 missing
SpDiam_EA.bo.numeric411 unique values
0 missing
SM11_AEA.ri.numeric410 unique values
0 missing
Eig01_EA.bo.numeric410 unique values
0 missing
Show all 71 features

107 properties

NumberOfInstances
887
Number of instances (rows) of the dataset.
NumberOfFeatures
71
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
70
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.22
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
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
CfsSubsetEval_DecisionStumpErrRate
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
CfsSubsetEval_DecisionStumpKappa
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
CfsSubsetEval_NaiveBayesAUC
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
CfsSubsetEval_NaiveBayesErrRate
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
CfsSubsetEval_NaiveBayesKappa
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
CfsSubsetEval_kNN1NAUC
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
CfsSubsetEval_kNN1NErrRate
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
CfsSubsetEval_kNN1NKappa
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
ClassEntropy
Entropy of the target attribute values.
DecisionStumpAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.08
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
144.27
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
392.75
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
10.73
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
126.77
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
20.07
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
11.8
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
1.69
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
3.77
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.39
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.2
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.52
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.07
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NaiveBayesAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
98.59
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
1.41
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
1.07
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.85
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.74
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.32
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
3.21
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
2.82
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.25
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.66
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
28.04
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
3.99
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
3.47
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
1.47
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

12 tasks

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4501
0 runs - estimation_procedure: 50 times Clustering
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