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Machine learningDeep learning / NLP / CV

Perceptron Berlapis Boleh Dijelaskan

Explainable Multilayer Perceptron (XMLP) ialah rangkaian saraf suapan hadapan (feedforward neural network) standard yang dilatih menggunakan kaedah backpropagation, ditambah dengan teknik kebolehterangan pasca-hoc (post-hoc interpretability techniques) — seperti nilai SHAP, LIME, atau integrated gradients — yang mengaitkan setiap ramalan kepada ciri input individu. Gabungan ini mengekalkan kuasa penghampiran MLP sambil memenuhi keperluan ketelusan yang lazim dalam domain yang dikawal selia atau berisiko tinggi.

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Sumber

  1. Lundberg, S. M., & Lee, S.-I. (2017). A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems, 30, 4765–4774. link
  2. Explainable artificial intelligence. Wikipedia. link

Cara memetik halaman ini

ScholarGate. (2026, June 3). Explainable Multilayer Perceptron (MLP with Post-hoc Interpretability). ScholarGate. https://scholargate.app/ms/deep-learning/explainable-multilayer-perceptron

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ScholarGateExplainable Multilayer Perceptron (Explainable Multilayer Perceptron (MLP with Post-hoc Interpretability)). Dicapai 2026-06-15 daripada https://scholargate.app/ms/deep-learning/explainable-multilayer-perceptron · Set data: https://doi.org/10.5281/zenodo.20539026