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请教一下,当数据量比较大时:100w用户,2w物品,900万行评分,矩阵密度:0.05% 这样的数据量应该怎么处理呢?目前使用BiasedMFRecommender,25G内存都不够用,计算不出来。
The text was updated successfully, but these errors were encountered:
这个就是个demo,你的数据量不小了,25g铁定不够用老铁,你物品都两万了 算物品的相似度你25g都够呛,减少数据量本着可以跑通的原则来吧
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请教一下,当数据量比较大时:100w用户,2w物品,900万行评分,矩阵密度:0.05%
这样的数据量应该怎么处理呢?目前使用BiasedMFRecommender,25G内存都不够用,计算不出来。
The text was updated successfully, but these errors were encountered: