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Phen

Phen

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Author: Source: Unknown - Date unknown Please cite: This is one of 41 drug design datasets. The datasets with 1143 features are formed using Adriana.Code software (www.molecular-networks.com/software/adrianacode). The molecules and outputs are taken from the original studies (see below). The other datasets are taken exactly from the original studies. The last attribute in each file is the target. Original studies: carbolenes "B. D. Silverman and Daniel. E. Platt, J. Med. Chem. 1996, 39, 2129-2140" mtp2 "Bergstrom, C. A. S.; Norinder, U.; Luthman, K.; Artursson, P. Molecular Descriptors Influencing Melting Point and Their Role in Classification of Solid Drugs. J. Chem. Inf. Comput. Sci.; (Article); 2003; 43(4); 1177-1185" chang, cristalli, depreux, doherty, garrat2, garrat, heyl, krystek, lewis, penning, rosowsky, siddiqi, stevenson, strupcz, svensson, thompson, tsutumi, uejling, yokoyama1, yokoyama2 "David E Patterson, Richard D Cramer, Allan M Ferguson, Robert D Clark, Laurence W Weinberger. Neighbourhood Behaviour: A Useful Concept for Validation of ""Molecular Diversity"" Descriptors. J. Med. Chem. 1996 (39) 3049 - 3059." mtp "Karthikeyan, M.; Glen, R.C.; Bender, A. General melting point prediction based on a diverse compound dataset and artificial neural networks. J. Chem. Inf. Model.; 2005; 45(3); 581-590" benzo32 "Harrison,P.W. and Barlin,G.B. and Davies,L.P. and Ireland,S.J. and Matyus,P. and Wong,M.G., Syntheses, pharmacological evaluation and molecular modelling of substituted 6-alkoxyimidazo[1,2-b]pyridazines as new ligands for the benzodiazepine receptor, European Journal of Medicinal Chemistry, (31), 1996, 651-662" PHENETYL1 "H. Kubinyi (Ed.): ""QSAR: Hansch Analysis and Related Approaches"", VCH, Weinhein (Ger), 1993, pp.57-68" pah "Todeschini, R.; Gramatica, P.; Marengo, E.; Provenzani, R. Weighted Holistic Invariant Molecular Descriptors. Part 2. Theory Development and Applications on Modeling Physico-Chemical Properties of PolyAromatic Hydrocarbons (PAH). Chemom. Intell. Lab. Syst. 1995, 27, 221-229." pdgfr "R. Guha and P. Jurs. The Development of Linear, Ensemble and Non-linear Models for the Prediction and Interpretation of the Biological Activity of a Set of PDGFR Inhibitors. J. Chem. Inf. Comput. Sci. 2004, 44 (6), 2179-2189" Phen "Cammarata, A. Interrelationship of the Regression Models Used for Structure-Activity Analyses. J. Med. Chem. 1972, 15, 573-577" topo_2_1, yprop_4_1 "Jun Feng et al, Predictive Toxicology: Benchmarking Molecular Descriptors and Statistical Methods, J. Chem. Inf Comput. Sci., 2003 (43) 1463-1470" qsabr1, qsabr2 "Damborsky, J., Schultz, T.W., Comparison of the QSAR models for toxicity and biodegradability of anilines and phenols, Chemosphere 34: 429-446, 1997" qsartox "Blaha, L., Damborsky, J., Nemec, M., QSAR for acute toxicity of saturated and unsaturated halogenated aliphatic compounds, Chemosphere 36: 1345-1365, 1998" qsbr_rw1 "Damborsky, J. et al., Structure-biodegradability relationships for chlorinated dibenzo-p-dioxins and dibenzofurans, In: Wittich, R.-M., Biodegradation of dioxins and furans, R.G. Landes Company, Austin, 1998" qsbr_y2 "Damborsky, J. et al., A mechanistic approach to deriving QSBR- A case study: dehalogenation of haloaliphatic compounds, In: Peijnenburg, W.J.G.M., Damborsky, J., Biodegradability Prediction, Kluwer Academic Publishers" qsbralks "Damborsky, J. et al., Mechanism-based Quantitative Structure-Biodegradability Relationships for hydrolytic dehalogenation of chloro- and bromo-alkenes, Quantitative Structure-Activity Relationships 17: 450-458, 1998" qsfrdhla "Damborsky, J., Quantitative structure-function relationships of the single-point mutants of haloalkane dehalogenase: A multivariate approach, Qunatitative Structure-Activity Relationships 16: 126-135, 1997" qsfsr1 "Damborsky, J., Quantitative structure-function and structure-stability relationships of purposely modified proteins, Protein Engineering 11: 21-30, 1998" qsfsr2 "Damborsky, J., Quantitative structure-function and structure-stability relationships of purposely modified proteins, Protein Engineering 11: 21-30, 1998" qsprcmpx "Cajan, M. et al., Stability of Aromatic Amides with Bromide Anion: Quantitative Structure-Property Relationships, Journal of Chemical Information and Computer Sciences, in press, 2000" selwood "Selwood, D. L.; Livingstone, D. J.; Comley, J. C.; O'Dowd, A. B.; Hudson, A. T.; Jackson, P.; Jandu, K. S.; Rose, V. S.; Stables, J. N. Structure-Activity Relationships of Antifilarial Antimycin Analogues: A Multivariate Pattern Recognition Study J. Med. Chem., 1990, 33, 136-142"

111 features

oz111 (target)numeric19 unique values
0 missing
oz1numeric3 unique values
0 missing
oz2numeric15 unique values
0 missing
oz3numeric3 unique values
0 missing
oz4numeric15 unique values
0 missing
oz5numeric3 unique values
0 missing
oz6numeric3 unique values
0 missing
oz7numeric3 unique values
0 missing
oz8numeric3 unique values
0 missing
oz9numeric3 unique values
0 missing
oz10numeric14 unique values
0 missing
oz11numeric3 unique values
0 missing
oz12numeric3 unique values
0 missing
oz13numeric4 unique values
0 missing
oz14numeric4 unique values
0 missing
oz15numeric4 unique values
0 missing
oz16numeric4 unique values
0 missing
oz17numeric22 unique values
0 missing
oz18numeric4 unique values
0 missing
oz19numeric22 unique values
0 missing
oz20numeric4 unique values
0 missing
oz21numeric4 unique values
0 missing
oz22numeric4 unique values
0 missing
oz23numeric4 unique values
0 missing
oz24numeric4 unique values
0 missing
oz25numeric4 unique values
0 missing
oz26numeric4 unique values
0 missing
oz27numeric4 unique values
0 missing
oz28numeric4 unique values
0 missing
oz29numeric4 unique values
0 missing
oz30numeric4 unique values
0 missing
oz31numeric4 unique values
0 missing
oz32numeric4 unique values
0 missing
oz33numeric4 unique values
0 missing
oz34numeric3 unique values
0 missing
oz35numeric19 unique values
0 missing
oz36numeric21 unique values
0 missing
oz37numeric14 unique values
0 missing
oz38numeric20 unique values
0 missing
oz39numeric20 unique values
0 missing
oz40numeric4 unique values
0 missing
oz41numeric22 unique values
0 missing
oz42numeric22 unique values
0 missing
oz43numeric14 unique values
0 missing
oz44numeric22 unique values
0 missing
oz45numeric21 unique values
0 missing
oz46numeric22 unique values
0 missing
oz47numeric21 unique values
0 missing
oz48numeric22 unique values
0 missing
oz49numeric22 unique values
0 missing
oz50numeric6 unique values
0 missing
oz51numeric15 unique values
0 missing
oz52numeric15 unique values
0 missing
oz53numeric15 unique values
0 missing
oz54numeric15 unique values
0 missing
oz55numeric12 unique values
0 missing
oz56numeric4 unique values
0 missing
oz57numeric4 unique values
0 missing
oz58numeric4 unique values
0 missing
oz59numeric2 unique values
0 missing
oz60numeric4 unique values
0 missing
oz61numeric4 unique values
0 missing
oz62numeric4 unique values
0 missing
oz63numeric4 unique values
0 missing
oz64numeric4 unique values
0 missing
oz65numeric4 unique values
0 missing
oz66numeric4 unique values
0 missing
oz67numeric4 unique values
0 missing
oz68numeric3 unique values
0 missing
oz69numeric3 unique values
0 missing
oz70numeric4 unique values
0 missing
oz71numeric3 unique values
0 missing
oz72numeric3 unique values
0 missing
oz73numeric4 unique values
0 missing
oz74numeric4 unique values
0 missing
oz75numeric3 unique values
0 missing
oz76numeric4 unique values
0 missing
oz77numeric6 unique values
0 missing
oz78numeric4 unique values
0 missing
oz79numeric3 unique values
0 missing
oz80numeric3 unique values
0 missing
oz81numeric3 unique values
0 missing
oz82numeric4 unique values
0 missing
oz83numeric4 unique values
0 missing
oz84numeric4 unique values
0 missing
oz85numeric4 unique values
0 missing
oz86numeric3 unique values
0 missing
oz87numeric4 unique values
0 missing
oz88numeric3 unique values
0 missing
oz89numeric4 unique values
0 missing
oz90numeric15 unique values
0 missing
oz91numeric15 unique values
0 missing
oz92numeric20 unique values
0 missing
oz93numeric22 unique values
0 missing
oz94numeric22 unique values
0 missing
oz95numeric22 unique values
0 missing
oz96numeric15 unique values
0 missing
oz97numeric12 unique values
0 missing
oz98numeric16 unique values
0 missing
oz99numeric18 unique values
0 missing
oz100numeric16 unique values
0 missing
oz101numeric19 unique values
0 missing
oz102numeric10 unique values
0 missing
oz103numeric10 unique values
0 missing
oz104numeric14 unique values
0 missing
oz105numeric17 unique values
0 missing
oz106numeric17 unique values
0 missing
oz107numeric17 unique values
0 missing
oz108numeric15 unique values
0 missing
oz109numeric4 unique values
0 missing
oz110numeric4 unique values
0 missing

107 properties

22
Number of instances (rows) of the dataset.
111
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.
111
Number of numeric attributes.
0
Number of nominal attributes.
Second quartile (Median) of entropy among attributes.
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.
0.3
Mean standard deviation of attributes of the numeric type.
-0.64
Second quartile (Median) of kurtosis among attributes of the numeric type.
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.
0.6
Second quartile (Median) of means among attributes of the numeric type.
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.
-2.15
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
8.56
Maximum kurtosis among attributes of the numeric type.
0.08
Minimum of means among attributes of the numeric type.
-0.35
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.78
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
5.05
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 instances having missing values.
Third quartile of entropy among attributes.
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.
-1.89
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
-0.08
Third quartile of kurtosis among attributes of the numeric type.
0.85
Average class difference between consecutive instances.
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
3.11
Maximum skewness among attributes of the numeric type.
0.24
Minimum standard deviation of attributes of the numeric type.
100
Percentage of numeric attributes.
0.72
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
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
0.46
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
0
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
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.
First quartile of entropy among attributes.
0.43
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
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
-0.26
Mean kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.81
First quartile of kurtosis among attributes of the numeric type.
0.31
Third quartile of standard deviation of attributes of the numeric type.
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
0.55
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.41
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
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
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
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.
-0.55
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.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.
0.28
First quartile of standard deviation of attributes of the numeric type.
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
-0.04
Mean skewness among attributes of the numeric type.

5 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: oz111
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: oz111
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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