Prediction of Pixel Density of Mobile Using Machine Learning

Mobile plays an important role in our daily life. Pixel Density affects the picture quality. This paper focus on getting high quality of picture and video of mobiles by predicting pixel density. So that we can get higher quality images and videos in low cost devices. To predict the pixel Density of mobile we use regression model of Machine Learning. Regression methods play a vital role in forecasting Pixel Density. This research concentrates on creating regression methods. Various regression models, including simple linear regression, Lasso and Ridge regression, Decision Tree regression , and Random Forest regression algorithm are employed to estimate the pixel density of mobile using screen resolution and diagonal size of mobile. Ultimately, regression models are proposed that can effectively predict the pixel density of mobile. The best regression model is identified by evaluating the Performance matrix.