Question 15
You are a data scientist working on a binary classification problem to predict whether customers will buy a product based on various features such as age, income, and browsing history. You decide to use LogisticRegression from scikit-learn for this task. After some experimentation, you notice that the model is overfitting the training data, resulting in poor performance on the validation set.
Which of the following actions should you take to mitigate overfitting in your Logistic Regression model?
from sklearn.linear_model import LogisticRegressionmodel = LogisticRegression(penalty='...', C=...)