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We show that neural networks can be trained to give a high accuracy for classifying the orientifold property and vacua based on the newly generated orientifold Calabi-Yau database with $h^{1,1}(X) \\leq 6$ arXiv:2111.03078. This indicates the orientifold symmetry may already be encoded in the polytope structure. 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We show that neural networks can be trained to give a high accuracy for classifying the orientifold property and vacua based on the newly generated orientifold Calabi-Yau database with $h^{1,1}(X) \\leq 6$ arXiv:2111.03078. This indicates the orientifold symmetry may already be encoded in the polytope structure. 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