a transfer learning regression model based on Kernel Mean Matching (KMM) algorithm


Keywords
kernel-mean-matching, kmm, transfer-learning
License
MIT
Install
pip install KMMTR==1.1.3

Documentation

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Python package - KMMTransferReg

A transfer learning regression model based on Kernel Mean Matching (KMM) algorithm

Written using Python, which is suitable for operating systems, e.g., Windows/Linux/MAC OS etc.

Installing / 安装

pip install KMMTR 

Checking / 查看

pip show KMMTR 

Updating / 更新

pip install --upgrade KMMTR

Template / 模版

Click Here

References / 参考文献

Huang, J., Gretton, A., Borgwardt, K., Schölkopf, B., & Smola, A. (2006). Correcting sample selection bias by unlabeled data. Advances in neural information processing systems, 19.

About / 更多

Maintained by Bin Cao. Please feel free to open issues in the Github or contact Bin Cao (bcao@shu.edu.cn) in case of any problems/comments/suggestions in using the code.


Transfer learning links

1 : Instance-based transfer learning

  • Instance selection (marginal distributions are same while conditional distributions are different) :

    TrAdaboost

  • Instance re-weighting (conditional distributions are same while marginal distributions are different) :

    KMM

2 : Feature-based transfer learning

  • Explicit distance:

    • case 1 : marginal distributions are same while conditional distributions are different:

      TCA(MMD based) ; DAN(MK-MMD based)

    • case 1 : conditional distributions are same while marginal distributions are different

      JDA

    • case 3 : Both marginal distributions and conditional distributions are different

      DDA

  • Implicit distance :

    DANN

3 : Parameter-based transfer learning

  • Pretraining + fine tune