 | cberner-KNNImproved-r |
I implemented KNN with learning to find the best K, using cosine similarity and similarity weighting for prediction. Also the prediction is clamped to the range [1,5] since we know that ratings are in that range.
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Existing runs on cberner-KNNImproved-r
1-6 of 6
| ID | Program | Dataset | User | Updated << | Status | Total time | Memory | Error |
|---|---|---|---|---|---|---|---|---|
| Run #2068 | cberner-KNNImproved-r | cs281amovielens | internal | 256d6h ago | done | 1s | 415M | 0.761 |
| Run #1336 | cberner-KNNImproved-r | movielens1m | jake | 292d22h ago | done | 1h29m | 833M | 0.905 |
| Run #1312 | cberner-KNNImproved-r | eachmovie-1to5 | lester | 295d1h ago | failed | 24m27s | 2010M | |
| Run #1231 | cberner-KNNImproved-r | eachmovie | lester | 297d18h ago | done | 1h28m | 1764M | 1.20 |
| Run #875 | cberner-KNNImproved-r | movielens100k | cberner | 302d12h ago | done | 5m26s | 143M | 0.942 |
| Run #874 | cberner-KNNImproved-r | collaborativefiltering-sample | cberner | 302d12h ago | done | 1s | 428M | 0.901 |
Program contents
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