So to set up the problem:
I have a data set that had labeled data like colour, brand and quality as independent variables and the dependent is RRP (price).
I have made a linear regression model using this data and can predict the dependent variable using the independent variables (i am using scikitlearn so just using model.predict. This is causing me siginificant problems and I'm not sure if this is the right way to deal with this and I'm not sure if this will hinder my goal of getting accurate values for predicted variables.
Is there a way to calculate the potential accuracy of the price that is predicted? It seems to me if I ask the model to predict on brand x and quality y and the model knows brand x and the quality always produces a tight range of prices the accuracy is potentially higher?