TY - JOUR AU - Moreira Cestari, Daniel AU - Mello, Rodrigo Fernandes de PY - 2020/04/03 Y2 - 2024/03/28 TI - Random Projections and α-Shape to Support the Kernel Design (Student Abstract) JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 34 IS - 10 SE - Student Abstract Track DO - 10.1609/aaai.v34i10.7211 UR - https://ojs.aaai.org/index.php/AAAI/article/view/7211 SP - 13877-13878 AB - <p>We demonstrate that projecting data points into hyperplanes is good strategy for general-purpose kernel design. We used three different hyperplanes generation schemes, random, convex hull and α-shape, and evaluated the results on two synthetic and three well known image-based datasets. The results showed considerable improvement in the classification performance in almost all scenarios, corroborating the claim that such an approach can be used as a general-purpose kernel transformation. Also, we discuss some connection with Convolutional Neural Networks and how such an approach could be used to understand such networks better.</p> ER -