Metadata-Version: 2.1
Name: mlfast
Version: 0.0.17
Summary: It's a Python machine learning package
Home-page: https://github.com/Abdul-Jaweed/mlfast
Author: Abdul-Jaweed
Author-email: jdgaming7320@gmail.com
License: MIT
Project-URL: Bug Tracker, https://github.com/Abdul-Jaweed/mlfast/issues
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: ensure==1.0.2
Provides-Extra: testing
Requires-Dist: pytest>=7.1.3; extra == "testing"
Requires-Dist: mypy>=0.971; extra == "testing"
Requires-Dist: flake8>=5.0.4; extra == "testing"
Requires-Dist: tox>=3.25.1; extra == "testing"
Requires-Dist: black>=22.8.0; extra == "testing"

## mlfast

This Python machine learning package is built on top of scikit-learn and provides a simple API for regression and classification modeling. The main function in this package is called Regression() and Classification() which takes in the following arguments:

`X`: The independent variables (features) of the data set

`y`: The dependent variable (target) of the data set

`model`: The name of the regression and classification algorithm to be used (e.g. `lr` for Linear Regression, or `rf` for Random Forest Classifier, etc.)

`scaler`: The name of the data scaler to be used (e.g. "standard" for StandardScaler, "robust" for RobustScaler, etc.)

`cat`: A boolean indicating [`True` or `False`] whether the data set has categorical variables that need to be one-hot encoded


- PYPI link for this package - [mlfast](https://pypi.org/project/mlfast/)
