def main():
begin_date = datetime.datetime(2014,11,18)
end_date = datetime.datetime(2014,12,17)
data_dir = utils.get_data_dir(utils.FLAG_TRAIN_TEST)
fraw_str = '%s/data_%s_%s' %(data_dir,begin_date.strftime('%m%d'),end_date.strftime('%m%d'))
cf_dir = utils.get_data_dir(utils.FLAG_CF)
frate_str = '%s/rate_buy_%s_%s' %(cf_dir,begin_date.strftime('%m%d'),end_date.strftime('%m%d'))
theta = 0.0
top_n =10
frs_str = '%s/cf_%s_%s_%.1f_%d' %(cf_dir,begin_date.strftime('%m%d'),end_date.strftime('%m%d'),theta,top_n)
"""
print >> sys.stdout,'[build_item_rate_data] doing...'
build_item_rate_data(fraw_str,frate_str,only_buy = True)
print >> sys.stdout,'[build_item_rate_data] done'
"""
user_ids_list,item_ids_list,user_ids_dict,item_ids_dict = compute_user_item_list(frate_str)
print >> sys.stdout,'user num %d' %(len(user_ids_list))
print >> sys.stdout,'item num %d' %(len(item_ids_list))
print >> sys.stdout,'[compute_user_item_list] done '
print >> sys.stdout,'[load_rate_data] doing...'
rate_matrix = load_rate_data(frate_str,user_ids_dict,item_ids_dict,theta)
print >> sys.stdout,'[load_rate_data] done...'
print >> sys.stdout,'[model_and_predict] doing...'
predict_matrix = model_and_predict(rate_matrix,user_ids_list,item_ids_list,top_n,frs_str)
print >> sys.stdout,'[model_and_predict] done...'
buy_date = datetime.datetime(2014,12,18)
fbuy_str = '%s/data_buy_%s'%(data_dir,buy_date.strftime('%m%d'))
utils.evaluate_res_except_history(frs_str,fbuy_str,True,fraw_str)
def main():
data_dir = utils.get_data_dir(utils.FLAG_TRAIN_TEST)
rule_dir = utils.get_data_dir(utils.FLAG_RULE)
fraw_str = '%s/data_%s_%s' %(data_dir,utils.DATE_BEGIN.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
fitem_str = '%s/item' %(data_dir)
fres_cate_str = '%s/test_candidate_nbr_cate_%s_%s' %(rule_dir,utils.DATE_SPLIT.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
fbuy_str = '%s/data_buy_%s'%(data_dir,utils.DATE_NEXT.strftime('%m%d'))
cn = CN(fraw_str,utils.DATE_SPLIT,fitem_str)
cn.candiate_with_user_nbr_cate(fres_cate_str)
utils.evaluate_res_except_history(fres_cate_str,fbuy_str,True,fraw_str)
def main():
data_dir = utils.get_data_dir(utils.FLAG_TRAIN_TEST)
cf_dir = utils.get_data_dir(utils.FLAG_CF)
rule_dir = utils.get_data_dir(utils.FLAG_RULE)
fraw_str = '%s/data_%s_%s' %(data_dir,utils.DATE_BEGIN.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
fitem_str = '%s/item' %(data_dir)
fres_cate_str = '%s/test_candidate_rule_cate_%s_%s' %(rule_dir,utils.DATE_SPLIT.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
fbuy_str = '%s/data_buy_%s'%(data_dir,utils.DATE_NEXT.strftime('%m%d'))
bcr = CR(fraw_str,utils.DATE_SPLIT,fitem_str)
bcr.candidate_items_by_recent_cate(fres_cate_str)
utils.evaluate_res_except_history(fres_cate_str,fbuy_str,True,fraw_str)
def main():
data_dir = utils.get_data_dir(utils.FLAG_TRAIN_TEST)
rule_dir = utils.get_data_dir(utils.FLAG_RULE)
fraw_str = '%s/data_%s_%s' %(data_dir,utils.DATE_BEGIN.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
fitem_str = '%s/item' %(data_dir)
fbuy_str = '%s/data_buy_%s'%(data_dir,utils.DATE_NEXT.strftime('%m%d'))
fcandiadate_str = '%s/candidate_user_%s_%s' %(rule_dir,utils.DATE_SPLIT.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
fuser_label_str = '%s/user_label_%s_%s' %(rule_dir,utils.DATE_BEGIN.strftime('%m%d'),utils.DATE_END.strftime('%m%d'))
#cluster_user(fraw_str,begin_date,fuser_label_str)
#candidate_with_user_cluster(fraw_str,utils.DATE_BEGIN,fitem_str,fcandiadate_str)
#candidate_with_user_nbr_history(fraw_str,utils.DATE_SPLIT,fitem_str,fcandiadate_str)
candiate_with_user_nbr_cate(fraw_str,utils.DATE_SPLIT,fitem_str,fcandiadate_str)
utils.evaluate_res_except_history(fcandiadate_str,fbuy_str,True,fraw_str)
