Heterogeneous Newton Boosting Machine
Project description
snapboost
Hetergeneous Newton Boosting Machine
- Instead of using only decision trees as learners like XGBoost and LightGBM, HNBM uses a combination of decision trees and ridge regressors to learn more complicated patterns in data.
Usage Instructions
-
This project is published on PyPI. To install package, run:
pip install snapboost
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
snapboost-0.1.2.tar.gz
(3.9 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file snapboost-0.1.2.tar.gz.
File metadata
- Download URL: snapboost-0.1.2.tar.gz
- Upload date:
- Size: 3.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.5.0 importlib_metadata/4.0.1 pkginfo/1.5.0.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b498f17cb6d6dbdc9bf5c6fc9d1f6f2e245e0af774324b596206acd9163cfb45
|
|
| MD5 |
7de74b86344ba8afd7d2ce069989edcd
|
|
| BLAKE2b-256 |
a4b95be949393a05ab9a3fa0fcf79b3722f3089421f37f75a865a02444f6fab5
|
File details
Details for the file snapboost-0.1.2-py3-none-any.whl.
File metadata
- Download URL: snapboost-0.1.2-py3-none-any.whl
- Upload date:
- Size: 4.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.5.0 importlib_metadata/4.0.1 pkginfo/1.5.0.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2a14216b7df1ef1ac10335391e8d26c85593d5cee336549528bc887797a49737
|
|
| MD5 |
ed448c8b54af309b7e269ff5d437241e
|
|
| BLAKE2b-256 |
4072948c19b75b066fed35efaab58fecacf3f0d7f4ad601b695d4a5b5590ecad
|
