Metadata-Version: 2.1
Name: regrez
Version: 1.0.2
Summary: Easiest way to implement linear regression.
Home-page: UNKNOWN
Author: Mehmet Utku OZTURK
Author-email: <contact@ælphard.tk>
License: UNKNOWN
Keywords: regression,machine learning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
Requires-Dist: matplotlib
Requires-Dist: sklearn
Requires-Dist: numpy
Requires-Dist: pandas

This is a simple Python package that aims to make using linear regression easier for programmers. For now, it only provides a simple linear regresion calculation that is based on one independent variable.

You can create a linear regression model as following:

``
from regrez import Model
m = Model("path/to/csv", "label for column that'll be used for x axis", "label for column that'll be used for y axis")
``

After that, you can train your model using ``m.Train()`` and test using ``m.Test(list_that_will_be_used_for_testing)``. Alternatively, there is a function called ``m.TrainAndTest()`` you can use if you only want to see how accurate would the model work. It separates 20% of the data for testing, trains the model with the rest of it, tests the model with separated data and shows how accurate your model is. You can use ``m.Visualize()`` after training if you want to see a plot showing both data points and the line to see how relative your variables are.

