A python package to perform quantile regression with more meaningful epistemic uncertainty estimates through training set augmentation using synthetic data. A blend of discriminative and generative models.
Project description
Project details
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
eqr-0.1.4.tar.gz
(15.3 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
eqr-0.1.4-py3-none-any.whl
(15.8 kB
view details)
File details
Details for the file eqr-0.1.4.tar.gz.
File metadata
- Download URL: eqr-0.1.4.tar.gz
- Upload date:
- Size: 15.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.3 CPython/3.12.5 Darwin/23.1.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
02ad0ab18084830d34eb6b3769ea4f5c3a40c7fdafa8df4550402b0bfdd9b076
|
|
| MD5 |
0bb3185f157e08a40371910279964d1d
|
|
| BLAKE2b-256 |
16e5ea5d42085eccf3a73194015f6f9e1691704ccb6f0d74355dca1aac07f096
|
File details
Details for the file eqr-0.1.4-py3-none-any.whl.
File metadata
- Download URL: eqr-0.1.4-py3-none-any.whl
- Upload date:
- Size: 15.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.3 CPython/3.12.5 Darwin/23.1.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
035f426b1a2235a830c903d79e72672610f38b5efda22f66bd5a6519f747ae4f
|
|
| MD5 |
4845d4b6d6b67c714dae8d8dfc6d8c2c
|
|
| BLAKE2b-256 |
126630963339794d892e740300956f8aafacdb4f3dc85c1cc868c01d70523571
|