IKNN Implicit

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

Parameter Search Space

Parameter Type Distribution Values Selected
max_nbrs Integer Uniform 2 ≤ \(x\) ≤ 50 49
min_nbrs Integer Uniform 1 ≤ \(x\) ≤ 5 1
min_sim Float LogUniform 1e-06 ≤ \(x\) ≤ 0.1 3.24e-05

Final Result

Searching selected the following configuration:

{'max_nbrs': 49, 'min_nbrs': 1, 'min_sim': 3.2370120322261394e-05}

With these metrics:

{
    'RBP': 0.20036862523883167,
    'LogRBP': 2.1866434870589586,
    'NDCG': 0.4035738853906182,
    'RecipRank': 0.3648774370574123,
    'TrainTask': 'b965cb2c-54b7-4e9a-9359-2043c38262c6',
    'TrainTime': 1.188541615032591,
    'TrainCPU': 1.076006,
    'TestTask': '0311af6d-3df6-4dbc-bf76-8825984cd333',
    'TestTime': 239.9054989729775,
    'TestCPU': 986.305329,
    'timestamp': 1746457520,
    'checkpoint_dir_name': None,
    'done': True,
    'training_iteration': 1,
    'trial_id': '80fcfce0',
    'date': '2025-05-05_11-05-20',
    'time_this_iter_s': 244.97985076904297,
    'time_total_s': 244.97985076904297,
    'pid': 4100890,
    'hostname': 'CCI-ws21',
    'node_ip': '10.248.127.152',
    'config': {'max_nbrs': 49, 'min_nbrs': 1, 'min_sim': 3.2370120322261394e-05},
    'time_since_restore': 244.97985076904297,
    'iterations_since_restore': 1,
    'experiment_tag': '64_max_nbrs=49,min_nbrs=1,min_sim=0.0000'
}

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.