Logistic regression is a classification algorithm used to predict binary outcomes. It models the probability of the outcome using a logistic function. Here's an example code snippet in Python using scikit-learn:
from sklearn.linear_model import LogisticRegression
# Example input features and target variable
X = [[2], [4], [5], [7]]
y = [0, 0, 1, 1]
# Create a logistic regression model
model = LogisticRegression()
# Fit the model to the data
model.fit(X, y)
# Predict the probabilities of the target variable for new inputs
new_X = [[3], [6]]
probabilities = model.predict_proba(new_X)
