Stop overkilling simple tasks with black-box models and use transparent models instead

• URL: http://arxiv.org/abs/2302.02804v3
• Date: Mon, 18 Sep 2023 14:34:27 GMT
• Title: Stop overkilling simple tasks with black-box models and use transparent models instead
• Authors: Matteo Rizzo, Matteo Marcuzzo, Alessandro Zangari, Andrea Gasparetto, Andrea Albarelli
• Abstract summary: Deep learning approaches are able to extract features autonomously from raw data. This allows for bypassing the feature engineering process. Deep learning strategies often outperform traditional models in terms of accuracy.
• Score: 57.42190785269343
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, the employment of deep learning methods has led to several significant breakthroughs in artificial intelligence. Different from traditional machine learning models, deep learning-based approaches are able to extract features autonomously from raw data. This allows for bypassing the feature engineering process, which is generally considered to be both error-prone and tedious. Moreover, deep learning strategies often outperform traditional models in terms of accuracy.

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