Customer Purchase Prediction Model Using Logistic Regression

[Mefisto04]

Pull Request Description:

This PR introduces a logistic regression model for predicting whether a customer will make a purchase based on their age and estimated salary. The model uses a dataset with columns for Age, EstimatedSalary, and Purchased (target variable).

Key steps include:

1. Loading customer data from a CSV file.
2. Preprocessing the data with feature scaling.
3. Splitting the dataset into training and testing sets.
4. Training the logistic regression model on the training data.
5. Evaluating the model's performance on the test data using accuracy score and confusion matrix.

Changes:

• Added logistic regression model for purchase prediction.
• Included preprocessing steps like data scaling (standardization).
• Implemented model evaluation using accuracy and confusion matrix.