Extrapolated Tree (ExtraTree)
ExtraTree implements extrapolated tree methods for regression, classification and density estimation based on pure python.
Contents
Installation
Via PypI
pip install ExtraTree
Via GitHub
pip install git+https://github.com/Karlmyh/ExtraTree.git
Mannul Install
git clone git@github.com:Karlmyh/ExtraTree.git
cd ExtraTree
python setup.py install
Metadata
Release files for ExtraTree 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ExtraTree-0.0.3.tar.gz | 16.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ExtraTree-0.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 40.4 kB
Release files / ExtraTree-0.0.3.tar.gz
| Download URL | ExtraTree-0.0.3.tar.gz |
|---|---|
| Size | 16.0 kB |
| Tags | Source |
|
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/4.0.1 CPython/3.8.2
|
Release files / ExtraTree-0.0.3-py3-none-any.whl
| Download URL | ExtraTree-0.0.3-py3-none-any.whl |
|---|---|
| Size | 24.4 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/4.0.1 CPython/3.8.2
|