Automated Machine Learning and Multi-Objective Optimization
This package allows to automatically create data-driven models for each output of a dataset and ,then, also automatically, use them as objective functions in a predefined multi-objective optimization problem to find out optimal values for the inputs.
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Release files for automlmoo 0.0.1.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| automlmoo-0.0.1.2.tar.gz | 4.3 kB | Without provenance | Details for automlmoo-0.0.1.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| automlmoo-0.0.1.2-py3-none-any.whl | Python 3 | none | any | Details for automlmoo-0.0.1.2-py3-none-any.whl |
Total release size: 9.7 kB
Release files / automlmoo-0.0.1.2.tar.gz
| Download URL | automlmoo-0.0.1.2.tar.gz |
|---|---|
| Size | 4.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.19
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Release files / automlmoo-0.0.1.2-py3-none-any.whl
| Download URL | automlmoo-0.0.1.2-py3-none-any.whl |
|---|---|
| Size | 5.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.19
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Security for automlmoo 0.0.1.2
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