Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2897

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2897

deactivated ARFF Publicly available Visibility: public Uploaded 14-07-2016 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: CHEMBL2897 (TID: 11047), and it has 92 rows and 1024 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent FCFP 1024-bit Molecular Fingerprints which were generated from SMILES strings. They were obtained using the Pipeline Pilot program, Dassault Systèmes BIOVIA. Generating Fingerprints do not usually require missing value imputation as all bits are generated.

1026 features

pXC50 (target)numeric25 unique values
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molecule_id (row identifier)nominal92 unique values
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FCFP4_1024b306numeric2 unique values
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FCFP4_1024b517numeric1 unique values
0 missing
FCFP4_1024b748numeric2 unique values
0 missing
FCFP4_1024b979numeric1 unique values
0 missing
FCFP4_1024b288numeric2 unique values
0 missing
FCFP4_1024b518numeric1 unique values
0 missing
FCFP4_1024b749numeric1 unique values
0 missing
FCFP4_1024b98numeric1 unique values
0 missing
FCFP4_1024b289numeric1 unique values
0 missing
FCFP4_1024b519numeric2 unique values
0 missing
FCFP4_1024b75numeric2 unique values
0 missing
FCFP4_1024b980numeric2 unique values
0 missing
FCFP4_1024b29numeric1 unique values
0 missing
FCFP4_1024b52numeric2 unique values
0 missing
FCFP4_1024b750numeric1 unique values
0 missing
FCFP4_1024b981numeric2 unique values
0 missing
FCFP4_1024b290numeric2 unique values
0 missing
FCFP4_1024b520numeric2 unique values
0 missing
FCFP4_1024b751numeric2 unique values
0 missing
FCFP4_1024b982numeric2 unique values
0 missing
FCFP4_1024b291numeric1 unique values
0 missing
FCFP4_1024b521numeric2 unique values
0 missing
FCFP4_1024b752numeric2 unique values
0 missing
FCFP4_1024b983numeric2 unique values
0 missing
FCFP4_1024b292numeric1 unique values
0 missing
FCFP4_1024b522numeric2 unique values
0 missing
FCFP4_1024b753numeric1 unique values
0 missing
FCFP4_1024b984numeric2 unique values
0 missing
FCFP4_1024b293numeric1 unique values
0 missing
FCFP4_1024b523numeric1 unique values
0 missing
FCFP4_1024b754numeric1 unique values
0 missing
FCFP4_1024b985numeric2 unique values
0 missing
FCFP4_1024b294numeric2 unique values
0 missing
FCFP4_1024b524numeric2 unique values
0 missing
FCFP4_1024b755numeric1 unique values
0 missing
FCFP4_1024b986numeric2 unique values
0 missing
FCFP4_1024b295numeric1 unique values
0 missing
FCFP4_1024b525numeric2 unique values
0 missing
FCFP4_1024b756numeric1 unique values
0 missing
FCFP4_1024b987numeric2 unique values
0 missing
FCFP4_1024b296numeric2 unique values
0 missing
FCFP4_1024b526numeric2 unique values
0 missing
FCFP4_1024b757numeric1 unique values
0 missing
FCFP4_1024b988numeric2 unique values
0 missing
FCFP4_1024b297numeric2 unique values
0 missing
FCFP4_1024b527numeric2 unique values
0 missing
FCFP4_1024b758numeric2 unique values
0 missing
FCFP4_1024b989numeric1 unique values
0 missing
FCFP4_1024b298numeric2 unique values
0 missing
FCFP4_1024b528numeric2 unique values
0 missing
FCFP4_1024b759numeric1 unique values
0 missing
FCFP4_1024b99numeric2 unique values
0 missing
FCFP4_1024b299numeric1 unique values
0 missing
FCFP4_1024b529numeric2 unique values
0 missing
FCFP4_1024b76numeric1 unique values
0 missing
FCFP4_1024b990numeric1 unique values
0 missing
FCFP4_1024b3numeric2 unique values
0 missing
FCFP4_1024b53numeric2 unique values
0 missing
FCFP4_1024b760numeric2 unique values
0 missing
FCFP4_1024b991numeric1 unique values
0 missing
FCFP4_1024b30numeric2 unique values
0 missing
FCFP4_1024b530numeric2 unique values
0 missing

107 properties

92
Number of instances (rows) of the dataset.
1026
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.
1025
Number of numeric attributes.
1
Number of nominal attributes.
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.
-2.04
Minimum kurtosis among attributes of the numeric type.
0.01
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
92
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
5.3
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
5.35
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
11.15
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.
0.1
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.
-9.59
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
9.59
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
92
Third quartile of kurtosis among attributes of the numeric type.
0.54
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
0.62
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
99.9
Percentage of numeric attributes.
0.03
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.
0.1
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
44.95
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.
9.59
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.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.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.05
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
11.06
First quartile of kurtosis among attributes of the numeric type.
0.18
Third quartile of standard deviation of attributes of the numeric type.
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
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
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
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
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
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.
3.58
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
5.98
Mean skewness among attributes of the numeric type.
0
First quartile of standard deviation of attributes of the numeric type.
Error rate 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.
0.12
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Kappa coefficient 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.
27.22
Second quartile (Median) of kurtosis among attributes of the numeric type.

12 tasks

3 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
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