Python RunRecommender.evaluate_hybrid_weights_validation Examples

Example #1

File: hyperopt_hybrid_SSLIM_CF_RP3beta.py Project: d1ggs/RecSys_Challenge-2019

def objective(params):
    print("\n############## New iteration ##############\n", params)
    if kfold:
        loss = - RunRecommender.evaluate_hybrid_weights_validation_kfold(recommender_list, params, kfold=N_KFOLD, parallelize_evaluation=kfold, parallel_fit=False)
    else:
        loss = - RunRecommender.evaluate_hybrid_weights_validation(hybrid, params)
    return loss

Example #2

def objective(params):
    print("Current parameters:")
    print(params)
    loss = - RunRecommender.evaluate_hybrid_weights_validation(hybrid, params)
    return loss