################################################# # # run experiments on trec100 data # # sample usage (from ipython console) # >> %run micro_finite_pool # ################################################## import os feature_sets = [ os.path.join("data", "micro_nutrients", s) for s in ["titles", "abstracts", "keywords", "title_concepts", "topic_dists"] ] import curious_snake # todo: make learner setup function parameteric so you can pass it in here curious_snake.run_experiments_finite_pool(feature_sets, os.path.join("output", "micro_finite"), num_runs=1)
import os #feature_sets = [os.path.join("data", "copd", s) for s in ["copd_combined"]] feature_sets = [os.path.join("data", "copd", s) for s in ["copd_labeled_terms_only"]] import curious_snake # todo: make learner setup function parameteric so you can pass it in here init_ids = eval(open(os.path.join("data", "copd", "init_ids"), 'r').readline()) curious_snake.run_experiments_finite_pool(feature_sets, os.path.join("output", "copd_labeled_features_AL"), num_runs=10, hold_out_p=.25,\ list_of_init_ids=init_ids)
################################################# # # run finite experiments on proton beam # ################################################## import os #feature_sets = [os.path.join("data", "proton_beam",s) for s in ["proton_titles", "proton_abstracts", "proton_keywords"]] #feature_sets = [os.path.join("data", "proton_beam", "old",s) for s in ["proton_titles", "proton_abstracts", "proton_keywords"]] #feature_sets = [os.path.join("data", "proton_beam",s) for s in ["proton_combined"]] feature_sets = [ os.path.join("data", "proton_beam", s) for s in ["proton_labeled_features"] ] init_ids = eval( open(os.path.join("data", "proton_beam", "init_ids"), 'r').readline()) import curious_snake # todo: make learner setup function parameteric so you can pass it in here curious_snake.run_experiments_finite_pool(feature_sets, os.path.join("output", "FAKER_labeled_features_proton_dux"),\ list_of_init_ids=init_ids, num_runs=10, upto=1000)
################################################# # # run experiments on trec100 data # # sample usage (from ipython console) # >> %run micro_finite_pool # ################################################## import os feature_sets = [ os.path.join("data", "micro_nutrients", s) for s in ["titles", "abstracts", "keywords", "title_concepts", "topic_dists"] ] import curious_snake # todo: make learner setup function parameteric so you can pass it in here curious_snake.run_experiments_finite_pool(feature_sets, os.path.join("output", "micro_finite"), num_runs=1)
################################################# # # sample usage (from ipython console) # >> %run micro_finite_pool # ################################################## import os # feature_sets = [os.path.join("data", "micro_nutrients",s) for s in ["abstracts"]] feature_sets = [os.path.join("data", "micro_nutrients", s) for s in ["micro_labeled_features_only"]] import curious_snake # todo: make learner setup function parameteric so you can pass it in here curious_snake.run_experiments_finite_pool( feature_sets, os.path.join("output", "micro_abstracts_finite_pool_labeled_feature_space"), num_runs=10, upto=2000 )
################################################# # # sample usage (from ipython console) # >> %run micro_finite_pool # ################################################## import os #feature_sets = [os.path.join("data", "micro_nutrients",s) for s in ["abstracts"]] feature_sets = [ os.path.join("data", "micro_nutrients", s) for s in ["micro_labeled_features_only"] ] import curious_snake # todo: make learner setup function parameteric so you can pass it in here curious_snake.run_experiments_finite_pool( feature_sets, os.path.join("output", "micro_abstracts_finite_pool_labeled_feature_space"), num_runs=10, upto=2000)
################################################# # # run finite experiments on proton beam # ################################################## import os #feature_sets = [os.path.join("data", "proton_beam",s) for s in ["proton_titles", "proton_abstracts", "proton_keywords"]] #feature_sets = [os.path.join("data", "proton_beam", "old",s) for s in ["proton_titles", "proton_abstracts", "proton_keywords"]] #feature_sets = [os.path.join("data", "proton_beam",s) for s in ["proton_combined"]] feature_sets = [os.path.join("data", "proton_beam",s) for s in ["proton_labeled_features"]] init_ids = eval(open(os.path.join("data", "proton_beam", "init_ids"), 'r').readline()) import curious_snake # todo: make learner setup function parameteric so you can pass it in here curious_snake.run_experiments_finite_pool(feature_sets, os.path.join("output", "FAKER_labeled_features_proton_dux"),\ list_of_init_ids=init_ids, num_runs=10, upto=1000)
import os #feature_sets = [os.path.join("data", "copd", s) for s in ["copd_combined"]] feature_sets = [ os.path.join("data", "copd", s) for s in ["copd_labeled_terms_only"] ] import curious_snake # todo: make learner setup function parameteric so you can pass it in here init_ids = eval(open(os.path.join("data", "copd", "init_ids"), 'r').readline()) curious_snake.run_experiments_finite_pool(feature_sets, os.path.join("output", "copd_labeled_features_AL"), num_runs=10, hold_out_p=.25,\ list_of_init_ids=init_ids)