小编Dav*_*her的帖子

我尝试使用 lightfm v.1.14 构建混合推荐系统。

我可以使用以下代码将所有数据放入稀疏矩阵中：

db = DBConnector().getDBConnector()
data = pd.read_sql('call get_UserItemRating();', con=db)

rows = data.loc[data['userID'].idxmax()]['userID'] + 1
cols = data.loc[data['itemID'].idxmax()]['itemID'] + 1
mat = sp.lil_matrix((rows, cols), dtype=np.int32)
for index, row in data.iterrows():
    if row['rating'] >= 4:
        mat[row['userID'], row['itemID']] = row['rating']

train = mat.tocoo()

data = pd.read_sql('SELECT * FROM wine_grapes;', con=db)
db.close()
rows = data.loc[data['fk_Wine'].idxmax()]['fk_Wine'] + 1
cols = data.loc[data['fk_Grapes'].idxmax()]['fk_Grapes'] + 1
mat = sp.lil_matrix((rows, cols), dtype=np.int32)
for index, row in data.iterrows():
    mat[row['fk_Wine'],row['fk_Grapes']] = 1

item_features = mat.tocoo()

model = …