Multilinear regression(MLR) is a trained regression model that can be used in making predictions. MLR is an extension of simple Linear regression. It takes more than one predictor variable to predict the response variable. This algorithm models the linear relationship between a single dependent continuous variable and more than one independent variable. It uses two or more independent variables to predict a dependent variable by fitting a best linear relationship.
It has two or more independent variables (X) and one dependent variable (y), where y is the value to be predicted
The main advantage of MLR is that it has the ability to determine the relative infuence of on eor more predictors to the target variable. Other data that can be used is othe rsoil nutrient parameters such as Organic Carbon(OC), Potassium(K) and Phosphorus (P) can be used to improve accuracy. Other factors such as algorithm tuning and choosing variables of high significance can be used to improve overall perfomance of the model