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Releases: shenweichen/DeepCTR

v0.6.1

08 Sep 08:57
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Major Features and Improvements

  • Fix bug in CCPM model that incorrectly using linear_feature_columns as DNN input features
  • Fix bug in DynamicGRU, a shape mismatch error will be caused in previous version when using DIEN with number of history_feature not equal to 2

v0.6.0

02 Aug 11:56
a0a2616
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Major Features and Improvements

  • Now DeepCTR is compatible with tensorflow 1.14 and 2.0.

v0.5.2

21 Jul 08:48
8182ea3
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Major Features and Improvements

Refactor Linear Layer

v0.5.1

10 Jul 01:59
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Major Features and Improvements

v0.5.0

30 Jun 14:35
bf210d7
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Major Features and Improvements

  • Refactor inputs module,now you can input different features to linear part and dnn part of the models.
  • Dense value inputs are concated with the inputs of dnn instead of embed into dense vectors.
  • previous versions of the code require modification to work properly,please refer new examples to update your codes.

v0.4.1

19 May 03:30
b787cdf
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Major Features and Improvements

v0.4.0

04 May 14:32
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Major Features and Improvements

  • Previous versions of the code require a little modification to work properly
  • Support feature hashing on the fly in training and inference process example
  • Add python2.7 support
  • Refactor methods in input_embedding.py
  • Refactor layers and models

API changes

  • deepctr.utils.SingleFeatand deepctr.utisl.VarlenFeat add new arguments to support feature hashing
  • deepctr.core.MLP to deepctr.core.DNN
  • arguments of all models and layers changes
v0.3.4 v0.4.0
l2_reg_deep l2_reg_dnn
activation dnn_activation
keep_prob dnn_dropout
hidden_size dnn_hidden_units
use_bn dnn_use_bn
final_activation task

v0.3.4

27 Apr 13:27
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Major Features and Improvements

v0.3.3

21 Apr 15:09
7d5bfd9
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Major Features and Improvements

v0.3.2

30 Mar 08:22
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Change Log

Major Features and Improvements