Parameter | Type | Distribution | Values | Selected |
---|---|---|---|---|
max_nbrs | Integer | Uniform | 2 ≤ \(x\) ≤ 50 | 47 |
min_nbrs | Integer | Uniform | 1 ≤ \(x\) ≤ 5 | 2 |
min_sim | Float | LogUniform | 1e-06 ≤ \(x\) ≤ 0.1 | 1e-05 |
UKNN Implicit
This page analyzes the hyperparameter tuning results for the ItemKNN scorer in implicit-feedback mode.
Parameter Search Space
Final Result
Searching selected the following configuration:
{'max_nbrs': 47, 'min_nbrs': 2, 'min_sim': 1.0017972543183347e-05}
With these metrics:
{ 'RBP': 0.23404099424134026, 'NDCG': 0.41976977802420784, 'RecipRank': 0.4162145784771224, 'TrainTask': 'ef35d789-466a-48e3-ac54-0e99446f4c9f', 'TrainTime': 0.1816444438882172, 'TrainCPU': 0.5365879999999997, 'TestTask': '1a506ba0-0be7-4bb7-9518-390f8b1e45be', 'TestTime': 1174.3037158311345, 'TestCPU': 3043.050819, 'timestamp': 1742787881, 'checkpoint_dir_name': None, 'done': True, 'training_iteration': 1, 'trial_id': '082be_00046', 'date': '2025-03-24_03-44-41', 'time_this_iter_s': 1177.607836484909, 'time_total_s': 1177.607836484909, 'pid': 3549206, 'hostname': 'cci-p102', 'node_ip': '10.246.250.62', 'config': {'max_nbrs': 47, 'min_nbrs': 2, 'min_sim': 1.0017972543183347e-05}, 'time_since_restore': 1177.607836484909, 'iterations_since_restore': 1, 'experiment_tag': '46_max_nbrs=47,min_nbrs=2,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.