#!flask/bin/python from src.recommender import SommelierYeungMFRecommender, SommelierRecommender y = SommelierYeungMFRecommender() y.split_data_evaluation([ {"steps":1000, "factors":10, "verbose":False}, ], percent_train=95) y.split_data_evaluation([ {"steps":1000, "factors":10, "verbose":False}, ], percent_train=90) y.split_data_evaluation([ {"steps":1000, "factors":10, "verbose":False}, ], percent_train=85) """ Test/train split: 90/10 Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8} NMAE 0.184606174037 MAE 0.923030870186 Total SD 0.74469464146 Author SDs {1: 0.66691197956843939, 2: 0.0, 3: 0.50279609651399249, 4: 0.57237094012612644, 5: 0.0, 10: 0.93620342958216529, 11: 0.57349908937180116, 12: 0.0, 13: 0.0, 14: 0.8401937215050671, 15: 0.19693957208969942, 16: 0.7473842558426278, 19: 0.79671806235540932} Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8} NMAE 0.177914688924 MAE 0.889573444621 Total SD 0.652182399073 Author SDs {1: 0.62928766408505432, 2: 0.0, 3: 0.59126553483873812, 4: 0.81513353713631542, 5: 0.0, 10: 0.07060409201739537, 11: 0.68872807551849069, 12: 0.0, 13: 0.0, 14: 0.62832339743318222, 15: 0.25462026420405665, 16: 0.41593979883552951, 19: 0.72265255016617702} Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8} NMAE 0.170369383859 MAE 0.851846919296 Total SD 0.718613078166 Author SDs {1: 0.59549749661482498, 2: 0.0, 3: 0.53760952462379241, 4: 0.65434050587508441, 5: 0.0, 10: 1.0949595865167969, 11: 0.65149354023737527, 12: 0.0, 13: 0.0, 14: 0.86791595910838881, 15: 0.30065848818498891, 16: 0.79978085141610344, 19: 0.31049227438073551} Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8}
#!flask/bin/python from src.recommender import SommelierYeungMFRecommender, SommelierRecommender y = SommelierYeungMFRecommender() y.split_data_evaluate_movielens_file('ml-100k/u.data', [ {"steps":1, "factors":10, "verbose":True}, {"steps":2, "factors":10, "verbose":True}, {"steps":3, "factors":10, "verbose":True}, {"steps":4, "factors":10, "verbose":True}, {"steps":5, "factors":10, "verbose":True}, {"steps":6, "factors":10, "verbose":True}, {"steps":7, "factors":10, "verbose":True}, {"steps":8, "factors":10, "verbose":True}, {"steps":9, "factors":10, "verbose":True}, {"steps":10, "factors":10, "verbose":True}, {"steps":12, "factors":10, "verbose":True}, {"steps":14, "factors":10, "verbose":True}, {"steps":16, "factors":10, "verbose":True}, ], percent_train=80) y.split_data_evaluate_movielens_file('ml-100k/u.data', [ {"steps":1, "factors":10, "verbose":True}, {"steps":2, "factors":10, "verbose":True}, {"steps":3, "factors":10, "verbose":True}, {"steps":4, "factors":10, "verbose":True}, {"steps":5, "factors":10, "verbose":True}, {"steps":6, "factors":10, "verbose":True}, {"steps":7, "factors":10, "verbose":True}, {"steps":8, "factors":10, "verbose":True}, {"steps":9, "factors":10, "verbose":True}, {"steps":10, "factors":10, "verbose":True}, {"steps":12, "factors":10, "verbose":True},
#!flask/bin/python from src.recommender import SommelierYeungMFRecommender, SommelierRecommender y = SommelierYeungMFRecommender() m = y.generate_lists_ui_matrix() y.multiple_factorizations(m, [ { "steps": 3500, "factors": 15 }, { "steps": 4000, "factors": 15 }, ]) y.multiple_factorizations(m, [ { "steps": 3500, "factors": 20 }, { "steps": 4000, "factors": 20 }, ])
#!flask/bin/python from src.recommender import SommelierYeungMFRecommender, SommelierRecommender y = SommelierYeungMFRecommender() y.split_data_evaluate_movielens_file('ml-100k/u.data', [ { "steps": 1, "factors": 10, "verbose": True }, { "steps": 2, "factors": 10, "verbose": True }, { "steps": 3, "factors": 10, "verbose": True }, { "steps": 4, "factors": 10, "verbose": True }, { "steps": 5, "factors": 10, "verbose": True }, {