mlr-gd Quickstart

Importing the Package

To import the package into your Python script:

import melar

About

The main component of mlr-gd is the LinearRegression class. This class is a complete model with methods for training and predicting. To use the class you initialize a new object assigned to a variable, optionally with arguments for configuring initial weights and biases, cost function and the amount of weights.

Example

Here is a quick example to demonstrate how to use mlr-gd:

import numpy as np
import melar

# Example data: y = x1 + 0.5*x2
x = np.array([[1, 3, 5, 8], [1, 2, 3, 6]])
y = np.array([1.5, 4, 6.5, 11])

learning_rate = 0.01
generations = 100

model = melar.LinearRegression(weights_amount=2)
model.train(x, y, learning_rate, generations, do_print=True)
print(f"Weights: {model.weights}, Bias: {model.bias}")