
We propose a method for decoding technical vehicle‘s parameters (make, model name, body type etc.) from its identification number. Classification is done for the entire specification at once, thus utilising the underlying dependencies between labels. To achieve the goal, several models were used – nearest neighbours, decision tree, extra trees and random forest classifiers.
decision tree classifier, k-nearest neighbours classifier, vehicle identification number, random forest classifier, extra trees classifier, multi-label classification
decision tree classifier, k-nearest neighbours classifier, vehicle identification number, random forest classifier, extra trees classifier, multi-label classification
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