Kernel Machines with stochastically motivated loss functions
Project description
Generalized Kernel Method
We connect generalized linear models (GLMs) with kernel methods (best known from Support Vector Machines) to obtain a generalized kernel method.
Installation
Usage
Theoretical Foundation
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
gkm-0.1.1.tar.gz
(18.3 kB
view details)
Built Distribution
gkm-0.1.1-py3-none-any.whl
(18.4 kB
view details)
File details
Details for the file gkm-0.1.1.tar.gz.
File metadata
- Download URL: gkm-0.1.1.tar.gz
- Upload date:
- Size: 18.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 6e29441d5db04dcb2a889c2fe3b00236778a47b8ba01779cd6d86617de87dc5b |
|
| MD5 | 191bcf8b02cb637c65997990751230d5 |
|
| BLAKE2b-256 | cfd85c8e7fd33dd4ded75484dc01abb5af2ffa213f1393b8146331f2c3348731 |
File details
Details for the file gkm-0.1.1-py3-none-any.whl.
File metadata
- Download URL: gkm-0.1.1-py3-none-any.whl
- Upload date:
- Size: 18.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b1b11f34083d9411559e57bd8c89ae151a2c6eb8c270b6a3ba099fea5545673b |
|
| MD5 | eade4ee43ac0ce86d5b87d1a02e12188 |
|
| BLAKE2b-256 | 8e385e3689dc8aaa8220f74544cbead2ae1c2356b48ac14bd8dd102d1518cf56 |
