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| 1 | from utils.datareader import Datareader | |
| 2 | from utils.submitter import Submitter | |
| 3 | from utils.post_processing import eurm_to_recommendation_list_submission | |
| 4 | import scipy.sparse as sps | |
| 5 | import numpy as np | |
| 6 | from utils.post_processing import eurm_remove_seed | |
| 7 | ||
| 8 | dr = Datareader(verbose = False, mode = "online", only_load = "False") | |
| 9 | sb = Submitter(dr) | |
| 10 | ||
| 11 | eurm = sps.load_npz("ensemble_per_cat_online_new_data_25_maggio.npz")
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| 12 | ||
| 13 | eurm_copy = eurm.copy() | |
| 14 | eurm_copy.data = np.ones(len(eurm_copy.data)) | |
| 15 | top_pop = eurm_copy.sum(axis=0).A1 | |
| 16 | ||
| 17 | - | eurm = sps.vstack([eurm[0:1000] + 0.1*top_pop, eurm[1000:]]) |
| 17 | + | eurm[0:1000] = eurm[0:1000] + 0.1*top_pop |
| 18 | eurm = eurm.tocsr() | |
| 19 | ||
| 20 | ||
| 21 | ||
| 22 | sps.save_npz("eurm_ensemble_per_cat_toppop_boosted_26_maggio", eurm)
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| 23 | ||
| 24 | sb.submit(recommendation_list=eurm_to_recommendation_list_submission(eurm), name="AAA_ensemble_normale_26_maggio", track="main", verify=True, gzipped=False) |
