Run nested cross-validation experiment on the CTRP drug sensitivity dataset, with the Gaussian + Gaussian (multivariate posterior) + Exponential model. ''' import sys, os project_location = os.path.dirname(__file__)+"/../../../../" sys.path.append(project_location) from BMF_Priors.code.models.bmf_gaussian_gaussian_exponential import BMF_Gaussian_Gaussian_Exponential from BMF_Priors.code.cross_validation.nested_matrix_cross_validation import MatrixNestedCrossValidation from BMF_Priors.data.drug_sensitivity.load_data import load_ctrp_ec50_integer ''' Settings BMF model. ''' method = BMF_Gaussian_Gaussian_Exponential R, M = load_ctrp_ec50_integer() hyperparameters = { 'alpha':1., 'beta':1., 'lamb':0.1 } train_config = { 'iterations' : 200, 'init' : 'random', } predict_config = { 'burn_in' : 180, 'thinning' : 1, } ''' Settings nested cross-validation. ''' K_range = [3,4,5,6,7] no_folds = 5 no_threads = 5
''' Run nested cross-validation experiment on the CTRP drug sensitivity dataset, with Poisson likelihood, Gamma priors, and Gamma hierarchical priors. ''' project_location = "/Users/thomasbrouwer/Documents/Projects/libraries/" import sys sys.path.append(project_location) from BMF_Priors.code.models.bmf_poisson_gamma_gamma import BMF_Poisson_Gamma_Gamma from BMF_Priors.code.cross_validation.nested_matrix_cross_validation import MatrixNestedCrossValidation from BMF_Priors.data.drug_sensitivity.load_data import load_ctrp_ec50_integer ''' Settings BMF model. ''' method = BMF_Poisson_Gamma_Gamma R, M = load_ctrp_ec50_integer() hyperparameters = {'a': 1., 'ap': 1., 'bp': 1.} train_config = { 'iterations': 200, 'init': 'random', } predict_config = { 'burn_in': 180, 'thinning': 1, } ''' Settings nested cross-validation. ''' K_range = [1, 2, 3] no_folds = 5 no_threads = 5 parallel = False folder_results = './results/poisson_gamma_gamma/' output_file = folder_results + 'results.txt'