Finding the accuracy of an AI model

Calculating the accuracy of the House Price prediction AI model

This table compares predicted house prices with actual house prices to evaluate the performance of the prediction model. For each property, the absolute error shows the difference between the predicted and actual values, while the error rate represents this difference as a proportion of the actual price.

The accuracy is calculated as 1 − error rate, which indicates how close each prediction is to the real value. A higher accuracy means the predicted price is closer to the actual house price.

Overall, the results show that most predictions have relatively low error rates and high accuracy, suggesting that the model performs reasonably well. However, a few cases show larger deviations, where the predicted price differs more significantly from the actual price, highlighting areas where the model could be improved.