task_dict = {'airfoil': 'reg', 'amazon_employee': 'cls', 'ap_omentum_ovary':'cls', 
             'bike_share': 'reg', 'german_credit': 'cls', 'higgs': 'cls',
             'housing_boston': 'reg', 'ionosphere': 'cls', 'lymphography': 'cls',
             'messidor_features': 'cls', 'openml_620': 'reg', 'pima_indian': 'cls',
             'spam_base': 'cls', 'spectf': 'cls', 'svmguide3': 'cls',
             'uci_credit_card': 'cls', 'wine_red': 'cls', 'wine_white': 'cls',
             'openml_586': 'reg', 'openml_589': 'reg', 'openml_607': 'reg',
             'openml_616': 'reg', 'openml_618': 'reg', 'openml_637': 'reg', 
             'smtp':'det', 'thyroid': 'det', 'yeast': 'det', 'wbc': 'det', 'mammography': 'det'
             }

task_type = {'reg', 'cls', 'det', 'rank'}

task_measure = {'reg': 'rae', 'cls': 'f1', 'det': 'ROC AUC Score', 'rank':'auprc'}