{ "data_id": "1039", "name": "hiva_agnostic", "exact_name": "hiva_agnostic", "version": 1, "version_label": null, "description": "**Author**: \n**Source**: Unknown - Date unknown \n**Please cite**: \n\nDatasets from the Agnostic Learning vs. Prior Knowledge Challenge (http:\/\/www.agnostic.inf.ethz.ch)\n\nDataset from: http:\/\/www.agnostic.inf.ethz.ch\/datasets.php\n\nModified by TunedIT (converted to ARFF format)\n\n\nHIVA is the HIV infection database\n\n\nThe task of HIVA is to predict which compounds are active against the AIDS HIV infection. The original data has 3 classes (active, moderately active, and inactive). We brought it back to a two-class classification problem (active vs. inactive). We represented the data as 2000 sparse binary input variables. The variables represent properties of the molecule inferred from its structure. The problem is therefore to relate structure to activity (a QSAR=quantitative structure-activity relationship problem) to screen new compounds before actually testing them (a HTS=high-throughput screening problem.)\n\nData type: non-sparse\nNumber of features: 1617\nNumber of examples and check-sum:\nPos_ex\tNeg_ex\tTot_ex\tCheck_sum\nTrain\t 135\t 3710\t 3845\t564954.00\nValid\t 14\t 370\t 384\t56056.00\n\n\nThis dataset contains samples from both training and validation datasets.", "format": "ARFF", "uploader": "Joaquin Vanschoren", "uploader_id": 2, "visibility": "public", "creator": "IJCNN 2007 Workshop on Agnostic Learning vs. Prior Knowledge", "contributor": null, "date": "2014-10-06 23:56:05", "update_comment": null, "last_update": "2014-10-06 23:56:05", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/53922\/hiva_agnostic.arff", "default_target_attribute": "label", "row_id_attribute": null, "ignore_attribute": null, "runs": 406, "suggest": { "input": [ "hiva_agnostic", "Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http:\/\/www.agnostic.inf.ethz.ch) Dataset from: http:\/\/www.agnostic.inf.ethz.ch\/datasets.php Modified by TunedIT (converted to ARFF format) HIVA is the HIV infection database The task of HIVA is to predict which compounds are active against the AIDS HIV infection. The original data has 3 classes (active, moderately active, and inactive). We brought it back to a two-class classification problem (active vs. inactive). 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