This project leverages machine learning techniques, specifically Support Vector Machine (SVM), to predict magazine purchases. The application features a user-friendly graphical interface developed using PyQt5 for seamless interaction.
Support Vector Machine (SVM) Algorithm: Utilizes the SVM algorithm for accurate prediction of magazine purchases based on historical data.
PyQt5 GUI: The graphical user interface allows users to input relevant parameters, triggering the machine learning model to predict the likelihood of magazine purchases.
Data Preprocessing: Implements data preprocessing techniques to ensure the model's accuracy and efficiency in predicting magazine purchase outcomes.
Model Evaluation: Utilizes various metrics to evaluate and validate the performance of the SVM model, providing insights into its predictive capabilities.
Python
Support Vector Machine (SVM)
PyQt5