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Why are categorical data all set 1?

See original GitHub issue

If do so,what`s the meaning of categorical data?

Issue Analytics

  • State:open
  • Created 5 years ago
  • Comments:5

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Lirunhuacommented, Dec 31, 2019

因为这里有 numerical feature, 所以对于整个输入的 vector, 不能直接 tf.nn.embedding_lookup 就完事了, 因为对于 numerical feature 没法做到真正的 embedding. 因此, 这里的做法是, 拿到 tf.nn.embedding_lookup 之后, 和输入的 vector 直接相乘一下. 对于 categorical feature, 我们当然是希望保持 embedding 对应索引的那个 vector. 所以就直接置为 1 了, 这个主要是代码的 trick 吧.

Lirunhuacommented, Dec 31, 2019

If do so,what`s the meaning of categorical data?

please note this line(, around line 88) self.y_first_order = tf.reduce_sum(tf.multiply(self.y_first_order, feat_value), 2) # None * F

It’s not for categorical feature, it’s for numercal feature

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