print("Loading movie ratings...") data = source.loadMovieLensRating() print("Prepare movie information...") source.computeMovieInformation() print("Creating ranking for each movie ...") rankings = source.getPopularityRanksByRating() return (source, data, rankings) np.random.seed(0) random.seed(0) # Load up common data set for the recommender algorithms (dataSource, data, rankings) = LoadData() # Construct an Evaluator to, you know, evaluate them evaluator = Evaluator(data, rankings) contentKNN = KNNAlgorithm() evaluator.AddAlgorithm(contentKNN, "ContentKNN") # Just make random recommendations # Random = NormalPredictor() # evaluator.AddAlgorithm(Random, "Random") evaluator.Evaluate() useTargetId = 85 totalMovieNeeded = 5 evaluator.GetRecomendationMovie(dataSource, useTargetId, totalMovieNeeded)