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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
## 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.
1 maintainer
Metadata
1 maintainer
Release files for KMMTR 1.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| KMMTR-1.1.3.tar.gz | 6.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| KMMTR-1.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.8 kB
Release files / KMMTR-1.1.3.tar.gz
| Download URL | KMMTR-1.1.3.tar.gz |
|---|---|
| Size | 6.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.12
|
Release files / KMMTR-1.1.3-py3-none-any.whl
| Download URL | KMMTR-1.1.3-py3-none-any.whl |
|---|---|
| Size | 6.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.12
|
