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CU Boulder/Northrop Grumman Capstone

Linear Regression

Linear regression is a prediction algorithm used in autonomous driving systems to model the relationship between input features and continuous output values, enabling the vehicle to make informed decisions based on real-time data.

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Algorithm Overview

Linear regression is a fundamental algorithm in the realm of supervised machine learning, particularly suited for predicting continuous values. In the context of autonomous driving, linear regression models the relationships between various input features such as speed, distance, and road conditions, and continuous output values like steering angle or braking force. By fitting a linear function to the input data, the algorithm establishes a predictive model that allows the vehicle to make informed decisions based on real-time data. Despite its simplicity, linear regression serves as a foundation for understanding more advanced prediction algorithms and offers a straightforward approach to solving certain problems in autonomous driving systems.