Predicting Auction Price of Vehicle License Plate with Deep Recurrent Neural Network
Table 2: Explaining Predictions with Automated Selection of Historical Examples
['Query and Predicted Price', 'Plate LZ3360', 'Price 1000', 'Plate MM293', 'Price 5000', 'Plate 13', 'Price 2182000']
The model was asked to predict the price of three plates, ranging from low to high value. The predicted prices are listed in the Prediction section, while the Historical Examples section lists for each query the top three entries returned by the k-NN model. Notice how the procedure focused on the numeric part for the low-value plate and the alphabetical part for the middle-value plate, reflecting the value of having identical digits and identical alphabets respectively. The procedure was also able to inform the user that a plate has been sold before. Finally, the examples provided for the high-value plate show why it is hard to obtain an accurate prediction for such plates, as the historical prices for similar plates are also highly variable.