按照官网上操作会报错

[wpinchine]

from scikits.crab import datasets

movies = datasets.load_sample_movies()
songs = datasets.load_sample_songs()
from scikits.crab.models import MatrixPreferenceDataModel

Build the model

model = MatrixPreferenceDataModel(movies.data)

from scikits.crab.metrics import pearson_correlation
from scikits.crab.similarities import UserSimilarity

Build the similarity

similarity = UserSimilarity(model, pearson_correlation)

from scikits.crab.recommenders.knn import UserBasedRecommender

Build the User based recommender

recommender = UserBasedRecommender(model, similarity, with_preference=True)

Recommend items for the user 5 (Toby)

recommender.recommend(5)