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For codes of the same length, theoretically, the further the coding distance between any two categories, the stronger the error correction capability. Therefore, when the code length is small, the theoretical optimal code can be calculated according to this principle. However, it is difficult to effectively determine the optimal code when the code length is slightly larger. In fact, this is an NP-hard problem. However, we usually do not need to obtain theoretical optimal codes, because non-optimal codes can often produce good enough classifiers in practice. On the other hand, it is not that the better the theoretical properties of coding, the better the classification performance, because the machine learning problem involves many factors, such as dismantling multiple classes into two "class subsets", and the difficulty of distinguishing the two class subsets formed by different dismantling methods is often different, that is, the difficulty of the two classification problems caused by them is different. Therefore, one theory has a good quality of error correction, but it leads to a difficult coding for the two-classification problem, which is worse than the other theory, but it leads to a simpler coding for the two-classification problem, and it is hard to say which is better or weaker in the final performance of the model.Episode 1三千万年前毁灭人类文明的遥远记忆，折磨着重新大古与迪迦奥特曼的神经……因为他手中握着最宝贵神奇的秘密。脸上依旧带着几分窃喜，却又有几分不甘与遗憾。在霓虹凡心这个故事中，当性和爱成为单调平凡的日常，出柜就已成为过往。 这个故事以五个同性恋挚友为主角，讲述他们如何在应对日常问题的同时体验爱，性以及友谊的含义。