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This GitHub repository showcases a Python project implementing insurance prediction through a multiple linear regression machine learning algorithm, featuring a PyQt5 graphical user interface for seamless user interaction.

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Eshwari30/Insurance-prediction

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Insurance Prediction with Multiple Linear Regression (Python + PyQt5)

Overview

This project is a Python-based application that utilizes the multiple linear regression algorithm to predict insurance charges. The application includes a graphical user interface (GUI) implemented with PyQt5 for an interactive user experience.

Features

Multiple Linear Regression Model: Utilizes machine learning to predict insurance costs based on multiple independent variables such as age, BMI, number of children, etc.

PyQt5 GUI: The application boasts an intuitive and interactive GUI built with PyQt5, enabling users to input data and obtain insurance predictions seamlessly.

Data Preprocessing: Incorporates data preprocessing steps to handle missing values, scale features, and ensure the model's accuracy.

Model Evaluation: Provides evaluation metrics to assess the performance of the multiple linear regression model.

Technologies Used

Python

scikit-learn (for machine learning)

PyQt5 (for GUI)

About

This GitHub repository showcases a Python project implementing insurance prediction through a multiple linear regression machine learning algorithm, featuring a PyQt5 graphical user interface for seamless user interaction.

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