Machine Learning Models with glass (Transparency)
Links: Github | PyPi - project
Installation: pip install spkit
Table of contents
-Logistic Regression -Naive Bayes -Decision Trees
Installation
Requirement: numpy, matplotlib
with pip
pip install mlglass
Build from the source
Download the repository or clone it with git, after cd in directory build it from source with
python setup.py install
Machine Learning models - with visualizations
- Logistic Regression
- Naive Bayes
- Decision Trees
- DeepNet (to be updated)
Machine Learning
Logistic Regression - View in notebook
Naive Bayes - View in notebook
Decision Trees - View in notebook
[source code] | [jupyter-notebook]
Plottng tree while training
Contacts:
PhD from Queen Mary University of London, Postdoctoral at University of East London
1 maintainer
Metadata
1 maintainer
Release files for mlglass 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mlglass-0.0.1.tar.gz | 18.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mlglass-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 36.5 kB
Release files / mlglass-0.0.1.tar.gz
| Download URL | mlglass-0.0.1.tar.gz |
|---|---|
| Size | 18.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
|
Release files / mlglass-0.0.1-py3-none-any.whl
| Download URL | mlglass-0.0.1-py3-none-any.whl |
|---|---|
| Size | 18.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
|
