Data Science, Machine Learning, Analytics, Time Series Analysis, Linear Regression.
In practical terms, it signifies how well the independent variables (features) in our model can explain the values of the dependent variable (target). An adjusted R-squared value of 86.19% can be considered a high value, considering what we are trying to model is housing prices, which can be