Тип публикации: статья из журнала

Год издания: 2024

Идентификатор DOI: 10.3390/bdcc8060068

Аннотация: <jats:p>This study proposes a method for classifying economic activity descriptors to match Nomenclature of Economic Activities (NACE) codes, employing a blend of machine learning techniques and expert evaluation. By leveraging natural language processing (NLP) methods to vectorize activity descriptors and utilizing genetic algoritПоказать полностьюhm (GA) optimization to fine-tune hyperparameters in multi-class classifiers like Naive Bayes, Decision Trees, Random Forests, and Multilayer Perceptrons, our aim is to boost the accuracy and reliability of an economic classification system. This system faces challenges due to the absence of precise target labels in the dataset. Hence, it is essential to initially check the accuracy of utilized methods based on expert evaluations using a small dataset before generalizing to a larger one.</jats:p>

Журнал: Big Data and Cognitive Computing

Выпуск журнала: Т. 8, № 6

Номера страниц: 68

ISSN журнала: 25042289

Издатель: MDPI AG

• Malashin Ivan (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia)
• Masich Igor (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia)
• Tynchenko Vadim (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia)
• Nelyub Vladimir (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia)
• Borodulin Aleksei (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia)
• Gantimurov Andrei (Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia)

• Ядро РИНЦ (eLIBRARY.RU)