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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1744528

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 by James
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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: CHEMBL1744528 (TID: 104109), and it has 10 rows and 162 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.

164 features

pXC50 (target)	numeric	8 unique values 0 missing
molecule_id (row identifier)	nominal	10 unique values 0 missing
ALOGP	numeric	10 unique values 0 missing
ALOGP2	numeric	10 unique values 0 missing
AMR	numeric	10 unique values 0 missing
ATS1m	numeric	10 unique values 0 missing
ATS1p	numeric	10 unique values 0 missing
ATS1s	numeric	10 unique values 0 missing
ATS1v	numeric	10 unique values 0 missing
ATS2m	numeric	10 unique values 0 missing
ATS2p	numeric	10 unique values 0 missing
ATS2s	numeric	10 unique values 0 missing
ATS2v	numeric	10 unique values 0 missing
ATS3m	numeric	10 unique values 0 missing
ATS3v	numeric	10 unique values 0 missing
ATS4m	numeric	10 unique values 0 missing
ATS4v	numeric	9 unique values 0 missing
ATS5m	numeric	10 unique values 0 missing
ATS5v	numeric	10 unique values 0 missing
ATS6m	numeric	10 unique values 0 missing
ATS6v	numeric	10 unique values 0 missing
ATS7m	numeric	10 unique values 0 missing
ATS8m	numeric	10 unique values 0 missing
ATS8v	numeric	10 unique values 0 missing
ATSC1s	numeric	10 unique values 0 missing
ATSC3e	numeric	10 unique values 0 missing
BBI	numeric	9 unique values 0 missing
BIC1	numeric	10 unique values 0 missing
BID	numeric	7 unique values 0 missing
BLTA96	numeric	9 unique values 0 missing
BLTD48	numeric	9 unique values 0 missing
BLTF96	numeric	8 unique values 0 missing
C.002	numeric	4 unique values 0 missing
C.006	numeric	4 unique values 0 missing
C.025	numeric	2 unique values 0 missing
CATS2D_01_LL	numeric	6 unique values 0 missing
CATS2D_02_LL	numeric	6 unique values 0 missing
CATS2D_03_LL	numeric	7 unique values 0 missing
CATS2D_06_AL	numeric	7 unique values 0 missing
CATS2D_07_AA	numeric	3 unique values 0 missing
CATS2D_07_LL	numeric	8 unique values 0 missing
CATS2D_08_LL	numeric	8 unique values 0 missing
CATS2D_09_AL	numeric	6 unique values 0 missing
CATS2D_09_LL	numeric	8 unique values 0 missing
CENT	numeric	9 unique values 0 missing
Chi1_AEA.bo.	numeric	9 unique values 0 missing
Chi1_AEA.dm.	numeric	9 unique values 0 missing
Chi1_AEA.ed.	numeric	9 unique values 0 missing
Chi1_AEA.ri.	numeric	9 unique values 0 missing
Chi1_EA	numeric	9 unique values 0 missing
Chi1_EA.ri.	numeric	10 unique values 0 missing
CIC0	numeric	10 unique values 0 missing
CIC1	numeric	10 unique values 0 missing
CID	numeric	9 unique values 0 missing
D.Dtr10	numeric	9 unique values 0 missing
DLS_01	numeric	3 unique values 0 missing
DLS_cons	numeric	5 unique values 0 missing
Dz	numeric	8 unique values 0 missing
Eig02_EA.bo.	numeric	7 unique values 0 missing
Eig03_AEA.bo.	numeric	8 unique values 0 missing
Eig03_AEA.ed.	numeric	8 unique values 0 missing
Eig03_AEA.ri.	numeric	9 unique values 0 missing
Eig03_EA	numeric	8 unique values 0 missing
Eig03_EA.ed.	numeric	8 unique values 0 missing
Eig03_EA.ri.	numeric	9 unique values 0 missing
Eig04_AEA.bo.	numeric	8 unique values 0 missing
Eig04_AEA.dm.	numeric	9 unique values 0 missing
Eig04_EA.bo.	numeric	8 unique values 0 missing
Eig05_AEA.bo.	numeric	9 unique values 0 missing
Eig05_AEA.ri.	numeric	10 unique values 0 missing
Eig05_EA	numeric	9 unique values 0 missing
Eig05_EA.bo.	numeric	9 unique values 0 missing
Eig05_EA.ri.	numeric	10 unique values 0 missing
Eig06_AEA.bo.	numeric	8 unique values 0 missing
Eig06_AEA.dm.	numeric	8 unique values 0 missing
Eig06_AEA.ed.	numeric	9 unique values 0 missing
Eig06_AEA.ri.	numeric	10 unique values 0 missing
Eig06_EA	numeric	9 unique values 0 missing
Eig06_EA.bo.	numeric	7 unique values 0 missing
Eig06_EA.ri.	numeric	10 unique values 0 missing
Eig07_AEA.bo.	numeric	8 unique values 0 missing
Eig07_AEA.ed.	numeric	9 unique values 0 missing
Eig07_AEA.ri.	numeric	10 unique values 0 missing
Eig07_EA	numeric	9 unique values 0 missing
Eig07_EA.bo.	numeric	8 unique values 0 missing
Eig07_EA.ed.	numeric	9 unique values 0 missing
Eig07_EA.ri.	numeric	10 unique values 0 missing
Eig08_AEA.bo.	numeric	9 unique values 0 missing
Eig08_AEA.ed.	numeric	9 unique values 0 missing
Eig08_AEA.ri.	numeric	10 unique values 0 missing
Eig08_EA.bo.	numeric	9 unique values 0 missing
Eig08_EA.ed.	numeric	9 unique values 0 missing
Eig08_EA.ri.	numeric	10 unique values 0 missing
Eig09_AEA.bo.	numeric	8 unique values 0 missing
Eig09_AEA.ed.	numeric	9 unique values 0 missing
Eig09_AEA.ri.	numeric	9 unique values 0 missing
Eig09_EA.bo.	numeric	8 unique values 0 missing
Eig09_EA.ed.	numeric	9 unique values 0 missing
Eig09_EA.ri.	numeric	9 unique values 0 missing
Eig10_AEA.bo.	numeric	9 unique values 0 missing
Eig10_AEA.ed.	numeric	9 unique values 0 missing
Eig10_EA.bo.	numeric	9 unique values 0 missing
Eig10_EA.ed.	numeric	9 unique values 0 missing
Eig11_AEA.bo.	numeric	9 unique values 0 missing
Eig11_AEA.ed.	numeric	8 unique values 0 missing
Eig11_AEA.ri.	numeric	10 unique values 0 missing
Eig11_EA	numeric	9 unique values 0 missing
Eig11_EA.bo.	numeric	9 unique values 0 missing
Eig11_EA.ed.	numeric	9 unique values 0 missing
Eig11_EA.ri.	numeric	10 unique values 0 missing
Eig12_AEA.bo.	numeric	9 unique values 0 missing
Eig12_AEA.ed.	numeric	9 unique values 0 missing
Eig12_AEA.ri.	numeric	10 unique values 0 missing
Eig12_EA	numeric	9 unique values 0 missing
Eig12_EA.bo.	numeric	8 unique values 0 missing
Eig12_EA.ed.	numeric	9 unique values 0 missing
Eig12_EA.ri.	numeric	10 unique values 0 missing
Eig13_AEA.bo.	numeric	7 unique values 0 missing
Eig13_AEA.ed.	numeric	9 unique values 0 missing
Eig13_AEA.ri.	numeric	7 unique values 0 missing
Eig13_EA	numeric	7 unique values 0 missing
Eig13_EA.bo.	numeric	6 unique values 0 missing
Eig13_EA.ed.	numeric	8 unique values 0 missing
Eig13_EA.ri.	numeric	7 unique values 0 missing
Eig14_AEA.bo.	numeric	9 unique values 0 missing
Eig14_AEA.ed.	numeric	8 unique values 0 missing
Eig14_EA.bo.	numeric	9 unique values 0 missing
Eig14_EA.ed.	numeric	9 unique values 0 missing
Eig15_AEA.ed.	numeric	8 unique values 0 missing
Eta_alpha	numeric	8 unique values 0 missing
Eta_alpha_A	numeric	8 unique values 0 missing
Eta_betaP_A	numeric	8 unique values 0 missing
Eta_F_A	numeric	10 unique values 0 missing
Eta_FL_A	numeric	9 unique values 0 missing
Eta_L_A	numeric	10 unique values 0 missing
GATS1i	numeric	9 unique values 0 missing
GATS1s	numeric	9 unique values 0 missing
GATS2i	numeric	10 unique values 0 missing
GATS2m	numeric	10 unique values 0 missing
GATS3m	numeric	10 unique values 0 missing
GATS3p	numeric	10 unique values 0 missing
GATS4i	numeric	10 unique values 0 missing
GATS4p	numeric	9 unique values 0 missing
GATS4v	numeric	10 unique values 0 missing
GATS5e	numeric	9 unique values 0 missing
GATS8i	numeric	10 unique values 0 missing
GATS8m	numeric	10 unique values 0 missing
GATS8v	numeric	10 unique values 0 missing
GGI10	numeric	9 unique values 0 missing
GGI7	numeric	9 unique values 0 missing
GGI9	numeric	8 unique values 0 missing
HDcpx	numeric	9 unique values 0 missing
IC1	numeric	10 unique values 0 missing
IDDM	numeric	9 unique values 0 missing
IDET	numeric	9 unique values 0 missing
IDM	numeric	9 unique values 0 missing
IDMT	numeric	9 unique values 0 missing
IVDM	numeric	9 unique values 0 missing
LLS_02	numeric	4 unique values 0 missing
LPRS	numeric	9 unique values 0 missing
MATS1i	numeric	10 unique values 0 missing
MATS1p	numeric	9 unique values 0 missing
MATS1v	numeric	9 unique values 0 missing
MATS3i	numeric	10 unique values 0 missing

Show first 100 features

107 properties

NumberOfInstances

Number of instances (rows) of the dataset.

NumberOfFeatures

164

Number of attributes (columns) of the dataset.

NumberOfClasses

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

163

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

AutoCorrelation

0.51

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

16.4

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

6.42

Maximum kurtosis among attributes of the numeric type.

MaxMeansOfNumericAtts

28710.51

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

2.15

Maximum skewness among attributes of the numeric type.

MaxStdDevOfNumericAtts

10189.37

Maximum standard deviation of attributes of the numeric type.

MeanAttributeEntropy

Average entropy of the attributes.

MeanKurtosisOfNumericAtts

-1.09

Mean kurtosis among attributes of the numeric type.

MeanMeansOfNumericAtts

207.56

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

0.07

Mean skewness among attributes of the numeric type.

MeanStdDevOfNumericAtts

70.61

Mean standard deviation of attributes of the numeric type.

MinAttributeEntropy

Minimal entropy among attributes.

MinKurtosisOfNumericAtts

-2.41

Minimum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

-5.82

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

-2.44

Minimum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

0.01

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

Number of binary attributes.

PercentageOfBinaryFeatures

Percentage of binary attributes.

PercentageOfInstancesWithMissingValues

Percentage of instances having missing values.

PercentageOfMissingValues

Percentage of missing values.

PercentageOfNumericFeatures

99.39

Percentage of numeric attributes.

PercentageOfSymbolicFeatures

0.61

Percentage of nominal attributes.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile1KurtosisOfNumericAtts

-1.93

First quartile of kurtosis among attributes of the numeric type.

Quartile1MeansOfNumericAtts

1.16

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

-0.19

First quartile of skewness among attributes of the numeric type.

Quartile1StdDevOfNumericAtts

0.12

First quartile of standard deviation of attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

Quartile2KurtosisOfNumericAtts

-1.51

Second quartile (Median) of kurtosis among attributes of the numeric type.

Quartile2MeansOfNumericAtts

2.99

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

0.01

Second quartile (Median) of skewness among attributes of the numeric type.

Quartile2StdDevOfNumericAtts

0.29

Second quartile (Median) of standard deviation of attributes of the numeric type.

Quartile3AttributeEntropy

Third quartile of entropy among attributes.

Quartile3KurtosisOfNumericAtts

-0.83

Third quartile of kurtosis among attributes of the numeric type.

Quartile3MeansOfNumericAtts

4.72

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

0.44

Third quartile of skewness among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

0.66

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-CHEMBL1744528

2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50

Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1744528

0 runs

Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1744528