regrez 2.1.9

Easiest way to implement linear regression.

This is a simple Python package that aims to make using linear regression easier for programmers.

You can create a simple linear regression model as following:

from regrez import Models

m = Models.Simple("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(test_x, test_y). 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.

You can create a multiple regression model as following:

from regrez import Models
m = Models.Multiple("path/to/csv", ["X Label 1", "X Label 2", "X Label 3"], ["Y Label"])

After that, you can train your model using m.Train() and test using m.Test(test_x, test_y). 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. There is no m.Visualize() for multiple linear regression models.