AMLBID is a Python-Package representing a meta learning-based framework for automating the process of algorithm selection, and hyper-parameter tuning in supervised machine learning. Being meta-learning based, the framework is able to simulate the role of the machine learning expert as a decision support system. In particular, AMLBID is considered the first complete, transparent and auto-explainable AutoML system for recommending the most adequate ML configuration for a problem at hand, and explain the rationale behind the recommendation and analyzing the predictive results in an interpretable and faithful manner through an interactive multiviews artifact.
A deployed example can be found at https://colab.research.google.com/drive/1zpMdccwRsoWe8dmksp_awY5qBgkVwsHd?usp=sharing
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Release files for AMLBID 0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| AMLBID-0.3.tar.gz | 1.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| AMLBID-0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.7 MB
Release files / AMLBID-0.3.tar.gz
| Download URL | AMLBID-0.3.tar.gz |
|---|---|
| Size | 1.3 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.7
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Release files / AMLBID-0.3-py3-none-any.whl
| Download URL | AMLBID-0.3-py3-none-any.whl |
|---|---|
| Size | 1.4 MB |
| Tags | Python 3 |
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twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.7
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