Predicting User Parking Preferences: An SVM Model with Bernoulli Distribution

Abstract

The number of motor vehicles are adding at rapid-fire pace from time to time and caused numerous problems to peoples like business jam and parking problems. This occurs due to the challenges associated with finding available parking sports. So, this exploration paper proposes a system for prognosticating stoner preferences between online and offline parking using a Support Vector Machine (SVM) model with Bernoulli distribution. The study aims to identify factors that impact druggies' preferences towards online and offline parking, including Age, Gender, Distance, Cost and Preference. The SVM model with Bernoulli distribution is employed to classify stoner preferences grounded on these factors. The findings of this study can be useful for policymakers and parking service providers in developing strategies for perfecting parking services and enhancing stoner experience.