Logistic regression analysis Self-made with python

Introduction

I will do my best from today, aiming for 100 consecutive days, and I will implement something in python. I thought that if I could do even one every day, I could grow. At first, it will be implemented while watching the Udemy course, so I will change the value a little and publish it with a little ingenuity. ~~ Aiming for a growing crocodile in 100 days ... ~~

First day

Logistic regression

The logistic regression model is a model whose main purpose is classification. Guessing the plausibility of likelihood from numerical values, We will use the steepest descent method to maximize the likelihood function.

What to implement

With reference to Udemy's Artificial Intelligence / Machine Learning Engineer Training Course We will implement something that classifies whether or not it is a lifestyle-related disease based on the intake of tobacco and alcohol.

Guidelines

Using the odds for healthy people, we create a function of a synergistic model of risk, from which we derive a sigmoid function to build the model. Sigmoid function: 1/1 + e ^ -x Function of interest: x = β0 + β1 * x1 + β2 * x2

code

Click here for the actual code day1.py

Day 1 impression

I think the first day will take the longest. I will do my best without being discouraged. Thank you for your support.

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