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 | 0.0123 |
IKNN 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': 49, 'min_nbrs': 1, 'min_sim': 0.012257043366936223}
With these metrics:
{ 'RBP': 0.20036164265392892, 'NDCG': 0.403570584477069, 'RecipRank': 0.36504210172817975, 'TrainTask': '433c6c55-41a9-42c6-83f3-5d6ba01896f1', 'TrainTime': 0.9203632419994392, 'TrainCPU': 0.9195959999999999, 'TestTask': '986d6714-f880-449e-afd0-2ab6d81488c5', 'TestTime': 354.8347766950028, 'TestCPU': 429.839769, 'timestamp': 1743038348, 'checkpoint_dir_name': None, 'done': True, 'training_iteration': 1, 'trial_id': 'fa6f7_00021', 'date': '2025-03-26_21-19-08', 'time_this_iter_s': 359.0305850505829, 'time_total_s': 359.0305850505829, 'pid': 463868, 'hostname': 'CCI-ws21', 'node_ip': '10.248.127.152', 'config': {'max_nbrs': 49, 'min_nbrs': 1, 'min_sim': 0.012257043366936223}, 'time_since_restore': 359.0305850505829, 'iterations_since_restore': 1, 'experiment_tag': '21_max_nbrs=49,min_nbrs=1,min_sim=0.0123' }
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.