a transfer learning regression model based on Kernel Mean Matching (KMM) algorithm
Project description
🤝🤝🤝 Please star ⭐️ it for promoting open source projects 🌍 ! Thanks !
# 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
## 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.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file KMMTR-1.1.3.tar.gz.
File metadata
- Download URL: KMMTR-1.1.3.tar.gz
- Upload date:
- Size: 6.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 6d185157f8dd939de8e9f19279f7b658ec8b6265a7b9bf724b4716faccc62e7e |
|
| MD5 | b0d8042436ba44616b86b6d8315c246d |
|
| BLAKE2b-256 | d1dee5853296934a377ce8776d234905376de07b6a5195c28f384d825367f83a |
File details
Details for the file KMMTR-1.1.3-py3-none-any.whl.
File metadata
- Download URL: KMMTR-1.1.3-py3-none-any.whl
- Upload date:
- Size: 6.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f19b16e8593a0dd35fc3f47fefa108dfb1a104b449d6694baca4a317eda3ae74 |
|
| MD5 | b620cec3def3df702a0196c473798367 |
|
| BLAKE2b-256 | d69c08300079a5f8de0643c488d78445dde4d0bde59f6a124e8c55073a791152 |
