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QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628

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: CHEMBL2007628 (TID: 104486), and it has 165 rows and 67 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.

69 features

pXC50 (target)numeric128 unique values
0 missing
ATS7vnumeric149 unique values
0 missing
ATS5mnumeric153 unique values
0 missing
ATS7snumeric156 unique values
0 missing
ATS7pnumeric159 unique values
0 missing
ATS7mnumeric158 unique values
0 missing
ATS7inumeric156 unique values
0 missing
ATS7enumeric160 unique values
0 missing
ATS6vnumeric157 unique values
0 missing
ATS6snumeric153 unique values
0 missing
ATS6pnumeric159 unique values
0 missing
ATS6mnumeric158 unique values
0 missing
ATS6inumeric150 unique values
0 missing
ATS6enumeric157 unique values
0 missing
ATS5vnumeric156 unique values
0 missing
ATS5snumeric155 unique values
0 missing
ATS5pnumeric152 unique values
0 missing
ATS5inumeric151 unique values
0 missing
ATSC1mnumeric163 unique values
0 missing
ATSC2snumeric164 unique values
0 missing
ATSC2pnumeric163 unique values
0 missing
ATSC2mnumeric162 unique values
0 missing
ATSC2inumeric155 unique values
0 missing
ATSC2enumeric139 unique values
0 missing
ATSC1vnumeric158 unique values
0 missing
ATSC1snumeric164 unique values
0 missing
ATSC1pnumeric161 unique values
0 missing
ATS8enumeric160 unique values
0 missing
ATSC1inumeric143 unique values
0 missing
ATSC1enumeric119 unique values
0 missing
ATS8vnumeric153 unique values
0 missing
ATS8snumeric158 unique values
0 missing
ATS8pnumeric154 unique values
0 missing
ATS8mnumeric155 unique values
0 missing
ATS8inumeric155 unique values
0 missing
ARRnumeric80 unique values
0 missing
ATS2inumeric149 unique values
0 missing
ATS2enumeric154 unique values
0 missing
ATS1vnumeric144 unique values
0 missing
ATS1snumeric144 unique values
0 missing
ATS1pnumeric149 unique values
0 missing
ATS1mnumeric146 unique values
0 missing
ATS1inumeric148 unique values
0 missing
ATS1enumeric150 unique values
0 missing
ATS2mnumeric143 unique values
0 missing
AMWnumeric157 unique values
0 missing
AMRnumeric163 unique values
0 missing
ALOGP2numeric164 unique values
0 missing
ALOGPnumeric159 unique values
0 missing
AECCnumeric156 unique values
0 missing
AACnumeric136 unique values
0 missing
GATS2snumeric137 unique values
0 missing
ATS3snumeric153 unique values
0 missing
ATS5enumeric157 unique values
0 missing
ATS4vnumeric151 unique values
0 missing
ATS4snumeric156 unique values
0 missing
ATS4pnumeric149 unique values
0 missing
ATS4mnumeric155 unique values
0 missing
ATS4inumeric155 unique values
0 missing
ATS4enumeric156 unique values
0 missing
ATS3vnumeric153 unique values
0 missing
molecule_id (row identifier)nominal165 unique values
0 missing
ATS3pnumeric152 unique values
0 missing
ATS3mnumeric151 unique values
0 missing
ATS3inumeric151 unique values
0 missing
ATS3enumeric154 unique values
0 missing
ATS2vnumeric146 unique values
0 missing
ATS2snumeric152 unique values
0 missing
ATS2pnumeric146 unique values
0 missing
Show all 69 features

107 properties

NumberOfInstances
165
Number of instances (rows) of the dataset.
NumberOfFeatures
69
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
68
Number of numeric attributes.
NumberOfSymbolicFeatures
1
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
0.42
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
22.2
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
99.3
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
2.24
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
26.72
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
4.66
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
6.46
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
-1.07
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
1.63
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.63
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.12
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
-4.03
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.08
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
98.55
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
1.45
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.31
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
3.53
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
-1.69
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.27
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
3.56
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
3.96
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
-1.13
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.42
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
7.42
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
4.95
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
-0.16
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.78
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-CHEMBL2007628
2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2007628
0 runs - estimation_procedure: 50 times Clustering
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