Implements several boosting algorithms in Python
Project description
KTBoost
This package implements several boosting algorithm. In particular, this includes tree and kernel boosting as well as the combined KTBoost algorithm. The package supports both gradient and Newton boosting updates as well as a hybrid version of the two for trees. Further, the package implements several loss functions which inlucdes the Tobit likelihood (i.e. the Grabit model). The package is an extenion of scikit-learn and re-uses code from scikit-learn.
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
KTBoost-0.0.5.tar.gz
(45.9 kB
view details)
Built Distribution
KTBoost-0.0.5-py2-none-any.whl
(50.2 kB
view details)
File details
Details for the file KTBoost-0.0.5.tar.gz.
File metadata
- Download URL: KTBoost-0.0.5.tar.gz
- Upload date:
- Size: 45.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.19.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 7beaedb3f1564ed19f8ae0362e936167fbbedacd94fda9fad14e0bf6425f8b09 |
|
| MD5 | 752f9dc24ff32aea970a3fbbafadcfad |
|
| BLAKE2b-256 | 8dbbc7b8709964c561acaa42ee959688bbf8f30b65ac2bfbb844873555e7157b |
File details
Details for the file KTBoost-0.0.5-py2-none-any.whl.
File metadata
- Download URL: KTBoost-0.0.5-py2-none-any.whl
- Upload date:
- Size: 50.2 kB
- Tags: Python 2
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.19.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 565a8cede4e18af46e808b7ca9105c4ac73d31fefc3cce5953576986e8d48459 |
|
| MD5 | 5892b435242b6467a60fd5c5d4bd77d4 |
|
| BLAKE2b-256 | bbb1de434cff96fed5cbcebbff85bdb24034602bfe9489829b36e42282dae9c7 |
