Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105

deactivated ARFF Publicly available Visibility: public Uploaded 15-07-2016 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: CHEMBL4105 (TID: 17106), and it has 127 rows and 61 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.

63 features

pXC50 (target)numeric66 unique values
0 missing
molecule_id (row identifier)nominal127 unique values
0 missing
NaaNHnumeric3 unique values
0 missing
SaaNHnumeric48 unique values
0 missing
CATS2D_02_DLnumeric8 unique values
0 missing
CATS2D_03_DLnumeric6 unique values
0 missing
CATS2D_03_AAnumeric6 unique values
0 missing
SpMin1_Bh.p.numeric56 unique values
0 missing
SsssNnumeric87 unique values
0 missing
nPyrazinesnumeric2 unique values
0 missing
Hynumeric74 unique values
0 missing
P_VSA_s_5numeric6 unique values
0 missing
H.050numeric7 unique values
0 missing
nHDonnumeric7 unique values
0 missing
SAdonnumeric12 unique values
0 missing
SpDiam_EA.ed.numeric50 unique values
0 missing
C.029numeric3 unique values
0 missing
N.071numeric3 unique values
0 missing
nArNR2numeric3 unique values
0 missing
nCIRnumeric10 unique values
0 missing
Rbridnumeric5 unique values
0 missing
CATS2D_04_DLnumeric7 unique values
0 missing
SpDiam_AEA.bo.numeric50 unique values
0 missing
LOCnumeric54 unique values
0 missing
Rperimnumeric20 unique values
0 missing
C.006numeric8 unique values
0 missing
SpDiam_AEA.ed.numeric58 unique values
0 missing
Eig01_AEA.ed.numeric31 unique values
0 missing
Eig01_EA.ed.numeric43 unique values
0 missing
SM10_AEA.dm.numeric43 unique values
0 missing
SpMax_AEA.ed.numeric31 unique values
0 missing
SpMax_EA.ed.numeric43 unique values
0 missing
Eig01_AEA.ri.numeric48 unique values
0 missing
Eig01_EAnumeric46 unique values
0 missing
SM09_AEA.bo.numeric46 unique values
0 missing
SM10_EA.ed.numeric90 unique values
0 missing
SM11_EA.ed.numeric92 unique values
0 missing
SM12_EA.ed.numeric90 unique values
0 missing
SM13_EA.ed.numeric88 unique values
0 missing
SM14_EA.ed.numeric89 unique values
0 missing
SM15_EA.ed.numeric85 unique values
0 missing
SpDiam_AEA.ri.numeric73 unique values
0 missing
SpDiam_EAnumeric46 unique values
0 missing
SpMax_AEA.ri.numeric48 unique values
0 missing
SpMax_EAnumeric46 unique values
0 missing
SpMin1_Bh.v.numeric61 unique values
0 missing
SM11_EA.bo.numeric83 unique values
0 missing
piPC04numeric82 unique values
0 missing
TRSnumeric16 unique values
0 missing
MPC06numeric66 unique values
0 missing
MPC08numeric79 unique values
0 missing
RBFnumeric60 unique values
0 missing
nCICnumeric6 unique values
0 missing
piPC05numeric91 unique values
0 missing
MCDnumeric48 unique values
0 missing
MPC07numeric70 unique values
0 missing
C.002numeric6 unique values
0 missing
SM08_EA.ed.numeric93 unique values
0 missing
SM09_EA.ed.numeric94 unique values
0 missing
SM15_AEA.ed.numeric93 unique values
0 missing
Eig12_AEA.ed.numeric72 unique values
0 missing
MPC04numeric49 unique values
0 missing
piPC08numeric91 unique values
0 missing
Show all 63 features

62 properties

NumberOfInstances
127
Number of instances (rows) of the dataset.
NumberOfFeatures
63
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
62
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
MaxSkewnessOfNumericAtts
3.4
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.04
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.43
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
32.61
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-1.42
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
1.26
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
1.63
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal type.
MeanKurtosisOfNumericAtts
-0.23
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
8.63
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
-0.07
First quartile of skewness among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
0.26
First quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
-0.2
Average class difference between consecutive instances.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
ClassEntropy
Entropy of the target attribute values.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
-0.86
Second quartile (Median) of kurtosis among attributes of the numeric type.
Dimensionality
0.5
Number of attributes divided by the number of instances.
MeanSkewnessOfNumericAtts
0.24
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
4.68
Second quartile (Median) of means among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
1.59
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
0.06
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-2.03
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0.61
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
20.19
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-0.05
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
36.19
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
-0.24
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
98.41
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
11.09
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.21
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
1.59
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Show all 62 properties

12 tasks

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Clustering on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4105
0 runs - estimation_procedure: 50 times Clustering
Define a new task