{ "data_id": "46295", "name": "qsar_aquatic_toxicity", "exact_name": "qsar_aquatic_toxicity", "version": 1, "version_label": null, "description": "From original source:\n-----\n\nData set containing values for 8 attributes (molecular descriptors) of 546 chemicals used to predict quantitative acute aquatic toxicity towards Daphnia Magna..\n\nAdditional Information\n\nThis dataset was used to develop quantitative regression QSAR models to predict acute aquatic toxicity towards the fish Pimephales promelas (fathead minnow) on a set of 908 chemicals. to predict acute aquatic toxicity towards Daphnia Magna. LC50 data, which is the concentration that causes death in 50% of test D. magna over a test duration of 48 hours, was used as model response. The model comprised 8 molecular descriptors: TPSA(Tot) (Molecular properties), SAacc (Molecular properties), H-050 (Atom-centred fragments), MLOGP (Molecular properties), RDCHI (Connectivity indices), GATS1p (2D autocorrelations), nN (Constitutional indices), C-040 (Atom-centred fragments). Details can be found in the quoted reference: M. Cassotti, D. Ballabio, V. Consonni, A. Mauri, I. V. Tetko, R. Todeschini (2014). Prediction of acute aquatic toxicity towards daphnia magna using GA-kNN method, Alternatives to Laboratory Animals (ATLA), 42,31:41; doi: 10.1177\/026119291404200106\n\nHas Missing Values?\n\nNo\n-----", "format": "arff", "uploader": "Bruno Belucci Teixeira", "uploader_id": 30703, "visibility": "public", "creator": "\"Ballabio,Davide, Cassotti,Matteo, Consonni,Viviana, and Todeschini,Roberto\"", "contributor": "\"Bruno Belucci\"", "date": "2024-07-23 19:29:30", "update_comment": null, "last_update": "2024-07-23 19:29:30", "licence": "CC BY 4.0", "status": "active", "error_message": null, "url": "https:\/\/api.openml.org\/data\/download\/22120806\/dataset", "kaggle_url": null, "default_target_attribute": "8", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "qsar_aquatic_toxicity", "From original source: ----- Data set containing values for 8 attributes (molecular descriptors) of 546 chemicals used to predict quantitative acute aquatic toxicity towards Daphnia Magna.. Additional Information This dataset was used to develop quantitative regression QSAR models to predict acute aquatic toxicity towards the fish Pimephales promelas (fathead minnow) on a set of 908 chemicals. to predict acute aquatic toxicity towards Daphnia Magna. LC50 data, which is the concentration that caus " ], "weight": 5 }, "qualities": { "NumberOfInstances": 546, "NumberOfFeatures": 9, "NumberOfClasses": 0, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 9, "NumberOfSymbolicFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "PercentageOfMissingValues": 0, "AutoCorrelation": -0.4520697247706427, "PercentageOfNumericFeatures": 100, "Dimensionality": 0.016483516483516484, "PercentageOfSymbolicFeatures": 0, "MajorityClassPercentage": null, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0 }, "tags": [], "features": [ { "name": "8", "index": "8", "type": "numeric", "distinct": "515", "missing": "0", "target": "1", "min": "0", "max": "10", "mean": "5", "stdev": "2" }, { "name": "0", "index": "0", "type": "numeric", "distinct": "227", "missing": "0", "min": "0", "max": "347", "mean": "48", "stdev": "47" }, { "name": "1", "index": "1", "type": "numeric", "distinct": "210", "missing": "0", "min": "0", "max": "572", "mean": "59", "stdev": "68" }, { "name": "2", "index": "2", "type": "numeric", "distinct": "11", "missing": "0", "min": "0", "max": "18", "mean": "1", "stdev": "2" }, { "name": "3", "index": "3", "type": "numeric", "distinct": "405", "missing": "0", "min": "-6", "max": "9", "mean": "2", "stdev": "2" }, { "name": "4", "index": "4", "type": "numeric", "distinct": "342", "missing": "0", "min": "1", "max": "6", "mean": "2", "stdev": "1" }, { "name": "5", "index": "5", "type": "numeric", "distinct": "403", "missing": "0", "min": "0", "max": "3", "mean": "1", "stdev": "0" }, { "name": "6", "index": "6", "type": "numeric", "distinct": "9", "missing": "0", "min": "0", "max": "11", "mean": "1", "stdev": "1" }, { "name": "7", "index": "7", "type": "numeric", "distinct": "6", "missing": "0", "min": "0", "max": "11", "mean": "0", "stdev": "1" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }