## Modeling

We will explore a straightforward model known as **Logistic Regression**, which is a supervised machine learning algorithm designed for classification problems.

It is particularly useful for predicting **binary outcomes** (1 / 0, Yes / No, True / False) based on a set of independent variables. The algorithm constructs a model that calculates a **probability** for each potential outcome and makes predictions based on which outcome is most likely.

The model employs a **logistic function** to map input variables to probabilities that range between 0 and 1. While primarily used for binary classification, Logistic Regression can also be adapted for **multi-class** classification through the training of multiple binary classifiers and combining their outcomes. This method is widely utilized in various fields, including medical research, marketing, and social sciences.

# Task

- Import the
`LogisticRegression`

class. - Initialize the model.
- Use the correct method to fit the model.

Everything was clear?