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yprop_4_1

yprop_4_1

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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"

252 features

oz252 (target)numeric1336 unique values
0 missing
oz1numeric800 unique values
0 missing
oz2numeric26 unique values
0 missing
oz3numeric586 unique values
0 missing
oz4numeric1125 unique values
0 missing
oz5numeric15 unique values
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oz6numeric33 unique values
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oz7numeric8 unique values
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oz12numeric31 unique values
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oz21numeric1 unique values
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oz24numeric1 unique values
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oz25numeric1 unique values
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oz26numeric1 unique values
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oz27numeric3 unique values
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oz28numeric1 unique values
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oz29numeric5 unique values
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oz31numeric10 unique values
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oz32numeric5 unique values
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oz33numeric3 unique values
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oz34numeric3 unique values
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oz35numeric7 unique values
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oz36numeric5 unique values
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oz40numeric2 unique values
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oz42numeric2 unique values
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oz43numeric1 unique values
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oz44numeric1 unique values
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oz45numeric3 unique values
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oz46numeric2 unique values
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oz47numeric4 unique values
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oz48numeric3 unique values
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oz49numeric4 unique values
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oz50numeric2 unique values
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oz51numeric3 unique values
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oz52numeric1 unique values
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oz54numeric1 unique values
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oz55numeric5 unique values
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oz56numeric3 unique values
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oz57numeric5 unique values
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oz58numeric5 unique values
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oz59numeric5 unique values
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oz60numeric5 unique values
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oz61numeric4 unique values
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oz63numeric3 unique values
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oz64numeric3 unique values
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oz65numeric3 unique values
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oz66numeric6 unique values
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oz67numeric1 unique values
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oz68numeric3 unique values
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oz69numeric2 unique values
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oz70numeric4 unique values
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oz71numeric2 unique values
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oz72numeric3 unique values
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oz73numeric2 unique values
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oz74numeric3 unique values
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oz75numeric1 unique values
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oz76numeric3 unique values
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oz77numeric1 unique values
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oz78numeric3 unique values
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oz79numeric2 unique values
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oz80numeric5 unique values
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oz81numeric5 unique values
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oz82numeric4 unique values
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oz83numeric12 unique values
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oz84numeric8 unique values
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oz85numeric5 unique values
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oz86numeric1 unique values
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oz87numeric12 unique values
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oz88numeric1 unique values
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oz89numeric4 unique values
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oz90numeric3 unique values
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oz91numeric9 unique values
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oz92numeric7 unique values
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oz93numeric3 unique values
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oz94numeric1 unique values
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oz95numeric1 unique values
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oz96numeric2 unique values
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oz97numeric3 unique values
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oz98numeric4 unique values
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oz99numeric3 unique values
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oz100numeric2 unique values
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oz101numeric6 unique values
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oz102numeric4 unique values
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oz104numeric5 unique values
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oz105numeric3 unique values
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oz106numeric4 unique values
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oz107numeric2 unique values
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oz108numeric2 unique values
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oz109numeric1 unique values
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oz110numeric4 unique values
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oz111numeric2 unique values
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oz112numeric2 unique values
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oz113numeric2 unique values
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oz114numeric3 unique values
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oz115numeric2 unique values
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oz116numeric3 unique values
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oz117numeric3 unique values
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oz118numeric3 unique values
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oz119numeric5 unique values
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oz120numeric9 unique values
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oz121numeric7 unique values
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oz122numeric1 unique values
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oz123numeric3 unique values
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oz124numeric15 unique values
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oz125numeric27 unique values
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oz126numeric14 unique values
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oz127numeric31 unique values
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oz128numeric15 unique values
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oz129numeric7 unique values
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oz130numeric9 unique values
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oz131numeric14 unique values
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oz132numeric6 unique values
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oz133numeric15 unique values
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oz134numeric5 unique values
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oz135numeric2 unique values
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oz136numeric6 unique values
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oz137numeric7 unique values
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oz138numeric5 unique values
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oz139numeric4 unique values
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oz140numeric4 unique values
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oz141numeric5 unique values
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oz142numeric4 unique values
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oz143numeric4 unique values
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oz144numeric3 unique values
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oz145numeric3 unique values
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oz146numeric3 unique values
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oz147numeric6 unique values
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oz148numeric3 unique values
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oz149numeric31 unique values
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oz150numeric16 unique values
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oz151numeric14 unique values
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oz152numeric7 unique values
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oz153numeric9 unique values
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oz154numeric6 unique values
0 missing
oz155numeric3 unique values
0 missing
oz156numeric5 unique values
0 missing
oz157numeric6 unique values
0 missing
oz158numeric5 unique values
0 missing
oz159numeric6 unique values
0 missing
oz160numeric4 unique values
0 missing
oz161numeric3 unique values
0 missing
oz162numeric3 unique values
0 missing
oz163numeric5 unique values
0 missing
oz164numeric6 unique values
0 missing
oz165numeric11 unique values
0 missing
oz166numeric6 unique values
0 missing
oz167numeric3 unique values
0 missing
oz168numeric4 unique values
0 missing
oz169numeric3 unique values
0 missing
oz170numeric1 unique values
0 missing
oz171numeric58 unique values
0 missing
oz172numeric44 unique values
0 missing
oz173numeric10 unique values
0 missing
oz174numeric7 unique values
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oz175numeric14 unique values
0 missing
oz176numeric20 unique values
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oz177numeric28 unique values
0 missing
oz178numeric11 unique values
0 missing
oz179numeric7 unique values
0 missing
oz180numeric4 unique values
0 missing
oz181numeric12 unique values
0 missing
oz182numeric9 unique values
0 missing
oz183numeric13 unique values
0 missing
oz184numeric9 unique values
0 missing
oz185numeric10 unique values
0 missing
oz186numeric8 unique values
0 missing
oz187numeric1 unique values
0 missing
oz188numeric1 unique values
0 missing
oz189numeric1 unique values
0 missing
oz190numeric1 unique values
0 missing
oz191numeric3 unique values
0 missing
oz192numeric4 unique values
0 missing
oz193numeric4 unique values
0 missing
oz194numeric5 unique values
0 missing
oz195numeric5 unique values
0 missing
oz196numeric4 unique values
0 missing
oz197numeric10 unique values
0 missing
oz198numeric7 unique values
0 missing
oz199numeric6 unique values
0 missing
oz200numeric8 unique values
0 missing
oz201numeric5 unique values
0 missing
oz202numeric5 unique values
0 missing
oz203numeric5 unique values
0 missing
oz204numeric1 unique values
0 missing
oz205numeric1 unique values
0 missing
oz206numeric2 unique values
0 missing
oz207numeric6 unique values
0 missing
oz208numeric9 unique values
0 missing
oz209numeric9 unique values
0 missing
oz210numeric3 unique values
0 missing
oz211numeric5 unique values
0 missing
oz212numeric5 unique values
0 missing
oz213numeric6 unique values
0 missing
oz214numeric7 unique values
0 missing
oz215numeric5 unique values
0 missing
oz216numeric3 unique values
0 missing
oz217numeric4 unique values
0 missing
oz218numeric3 unique values
0 missing
oz219numeric6 unique values
0 missing
oz220numeric3 unique values
0 missing
oz221numeric4 unique values
0 missing
oz222numeric2 unique values
0 missing
oz223numeric1 unique values
0 missing
oz224numeric4 unique values
0 missing
oz225numeric4 unique values
0 missing
oz226numeric1 unique values
0 missing
oz227numeric1 unique values
0 missing
oz228numeric1 unique values
0 missing
oz229numeric1 unique values
0 missing
oz230numeric1 unique values
0 missing
oz231numeric3 unique values
0 missing
oz232numeric6 unique values
0 missing
oz233numeric5 unique values
0 missing
oz234numeric2 unique values
0 missing
oz235numeric5 unique values
0 missing
oz236numeric1 unique values
0 missing
oz237numeric1 unique values
0 missing
oz238numeric1 unique values
0 missing
oz239numeric1 unique values
0 missing
oz240numeric1 unique values
0 missing
oz241numeric3 unique values
0 missing
oz242numeric4 unique values
0 missing
oz243numeric3 unique values
0 missing
oz244numeric5 unique values
0 missing
oz245numeric1 unique values
0 missing
oz246numeric54 unique values
0 missing
oz247numeric1231 unique values
0 missing
oz248numeric501 unique values
0 missing
oz249numeric8379 unique values
0 missing
oz250numeric1773 unique values
0 missing
oz251numeric4638 unique values
0 missing

107 properties

8885
Number of instances (rows) of the dataset.
252
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.
252
Number of numeric attributes.
0
Number of nominal attributes.
96.03
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.
0.01
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.
-0.81
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
8885
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
8.29
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
1
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.
0.05
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
0.03
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.
-42.1
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
534.57
Third quartile of kurtosis among attributes of the numeric type.
0.97
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
94.26
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
100
Percentage of numeric attributes.
0.02
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
0.26
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.
20.68
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
670.88
Mean kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
25.98
First quartile of kurtosis among attributes of the numeric type.
0.07
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
0.04
Mean of means among attributes of the numeric type.
Error rate 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
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.
4.12
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.
0.02
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
15.3
Mean skewness among attributes of the numeric type.
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.
0.05
Mean standard deviation of attributes of the numeric type.

15 tasks

3 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: root_mean_squared_error - target_feature: oz252
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: oz252
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: oz252
0 runs - estimation_procedure: 33% Holdout set - target_feature: oz252
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
Define a new task