Corex featurization and modeling primitives for D3M envrionments
Featurization: (featurization with information regularization for continuous data (linear Gaussian model) and text (similar to LDA)) Corex continuous Corex text
Regression: (echo provides mutual information regularization: linear regression and neural network modeling primitives provided) EchoLinear EchoRegression EchoClassification
Release files for dsbox-corex 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dsbox_corex-1.2.0.tar.gz | 64.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dsbox_corex-1.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 143.5 kB
Release files / dsbox_corex-1.2.0.tar.gz
| Download URL | dsbox_corex-1.2.0.tar.gz |
|---|---|
| Size | 64.3 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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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10
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Release files / dsbox_corex-1.2.0-py3-none-any.whl
| Download URL | dsbox_corex-1.2.0-py3-none-any.whl |
|---|---|
| Size | 79.2 kB |
| Tags | Python 3 |
|
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/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10
|