This table shows how close the predicted house prices are to the actual house prices š š Each row compares one predicted value with the real value and then measures the mistake and accuracy.
TheĀ predicted house price column shows the price guessed by the model, while the actual house price column shows the real price. The error ABS column tells the absolute difference between the predicted and actual prices, meaning how much the prediction was off without using plus or minus. The error rate shows the size of the error compared to the actual price, written as a decimal. The accuracy column shows how correct the prediction is, where a higher value means better prediction. Finally, accuracy % shows the same accuracy but written as a percentage, which is easier to understand.
From the table, we can see that rows with smaller errors have higher accuracy percentages, like 97.30% and 96%, while rows with bigger errors have lower accuracy, such as 71.10% and 75.70%. This helps us understand how well the prediction model is performing and where it needs improvementĀ The total model's accuracy is 86.6%