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Model evaluation is very important since we need to understand how well our model is performing. In comparison to classification, performance of a regression model is slightly harder to determine because, unlike classification, it is almost impossible to predict the exact value of a target variable. Therefore, we need a way to calculate how close our prediction value is to the real value.
Therefore, we will be looking at some fundamental and important metrics such as MAE, MSE, RMSE and R-Squared which are used for regression problems!