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 15
min_nbrs Integer Uniform 1 ≤ \(x\) ≤ 5 1
min_sim Float LogUniform 1e-06 ≤ \(x\) ≤ 0.1 1e-05

Final Result

Searching selected the following configuration:

{'max_nbrs': 15, 'min_nbrs': 1, 'min_sim': 1.0038311424288548e-05}

With these metrics:

{
    'RBP': 0.0068541776634895735,
    'LogRBP': -1.188656964954487,
    'NDCG': 0.1688764501123795,
    'RecipRank': 0.02900252734872533,
    'RMSE': 0.8056762891494675,
    'TrainTask': 'f9a3311f-7936-4eba-b7fe-ba61c4826976',
    'TrainTime': 0.26979967998340726,
    'TrainCPU': 0.26215800000000006,
    'TestTask': '5388175d-491b-4b61-8123-5bb8919085fc',
    'TestTime': 9.355778297991492,
    'TestCPU': 9.382571,
    'timestamp': 1746440636,
    'checkpoint_dir_name': None,
    'done': True,
    'training_iteration': 1,
    'trial_id': 'e11a4_00062',
    'date': '2025-05-05_06-23-56',
    'time_this_iter_s': 10.668705463409424,
    'time_total_s': 10.668705463409424,
    'pid': 3631840,
    'hostname': 'CCI-ws21',
    'node_ip': '10.248.127.152',
    'config': {'max_nbrs': 15, 'min_nbrs': 1, 'min_sim': 1.0038311424288548e-05},
    'time_since_restore': 10.668705463409424,
    'iterations_since_restore': 1,
    'experiment_tag': '62_max_nbrs=15,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.