IKNN Explicit

This page analyzes the hyperparameter tuning results for the ItemKNN scorer in explicit-feedback mode.

Parameter Search Space

Parameter Type Distribution Values Selected
max_nbrs Integer Uniform 2 ≤ \(x\) ≤ 50 33
min_nbrs Integer Uniform 1 ≤ \(x\) ≤ 5 1
min_sim Float LogUniform 1e-06 ≤ \(x\) ≤ 0.1 0.000112

Final Result

Searching selected the following configuration:

{'max_nbrs': 33, 'min_nbrs': 1, 'min_sim': 0.00011233896035987445}

With these metrics:

{
    'RBP': 0.06468677507178473,
    'NDCG': 0.28933176954553647,
    'RecipRank': 0.11474467197079954,
    'RMSE': 0.7772726197796639,
    'TrainTask': 'c01f708e-d560-4de0-b54c-d2d552e31a4b',
    'TrainTime': 3.5360089559981134,
    'TrainCPU': 3.541308,
    'TestTask': 'b192b8e7-088f-4ac5-8223-8ab74b0960b0',
    'TestTime': 347.51123341199855,
    'TestCPU': 348.79742799999997,
    'timestamp': 1745443696,
    'checkpoint_dir_name': None,
    'done': True,
    'training_iteration': 1,
    'trial_id': '0383b_00006',
    'date': '2025-04-23_17-28-16',
    'time_this_iter_s': 362.1544907093048,
    'time_total_s': 362.1544907093048,
    'pid': 345240,
    'hostname': 'CCI-ws21',
    'node_ip': '10.248.127.152',
    'config': {'max_nbrs': 33, 'min_nbrs': 1, 'min_sim': 0.00011233896035987445},
    'time_since_restore': 362.1544907093048,
    'iterations_since_restore': 1,
    'experiment_tag': '6_max_nbrs=33,min_nbrs=1,min_sim=0.0001'
}

Parameter Behavior

Neighborhood Size

The neighborhood size is key argument to consider, let’s look at RMSE with repspect to that:

Filtering

There are two filtering parameters we also test — minimum neighbors and mininmum simialrity.