''' Created on April 27, 2018 @author: Edwin Simpson ''' from evaluation.experiment import Experiment import data.load_data as load_data import numpy as np output_dir = '../../data/bayesian_sequence_combination/output/ner/' regen_data = False gt, annos, doc_start, text, gt_nocrowd, doc_start_nocrowd, text_nocrowd, gt_task1_val, gt_val, doc_start_val, text_val, _ = \ load_data.load_ner_data(regen_data) # ------------------------------------------------------------------------------------------------ exp = Experiment(None, 9, annos.shape[1], None, max_iter=20) exp.save_results = True exp.opt_hyper = False #True best_bac_wm = 'bac_seq' #'unknown' # choose model with best score for the different BAC worker models best_bac_wm_score = -np.inf best_nu0factor = 0.1 best_diags = 1 best_factor = 1 best_acc_bias = 0 exp.alpha0_diags = best_diags exp.alpha0_factor = best_factor
''' Created on April 27, 2018 @author: Edwin Simpson ''' from evaluation.experiment import Experiment import data.load_data as load_data import numpy as np import os gt, annos, doc_start, text, gt_nocrowd, doc_start_nocrowd, text_nocrowd, gt_task1_val, gt_val, doc_start_val, text_val, _ = \ load_data.load_ner_data(False) # debug with subset ------- # s = 100 # idxs = np.argwhere(gt!=-1)[:s, 0] # gt = gt[idxs] # annos = annos[idxs] # doc_start = doc_start[idxs] # text = text[idxs] # gt_task1_val = gt_task1_val[idxs] # ------------------------- num_reps = 10 batch_frac = 0.03 AL_iters = 10 for rep in range(1, num_reps): output_dir = '../data/bayesian_sequence_combination/output/ner_al_super_new/' if not os.path.isdir(output_dir):