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黎章目光落到那张简易的木床上，看着那个风烛残年的老人：清癯的面庞，颧骨高耸，只剩一张皮包裹着头骨。Strategy mode refers to defining a series of algorithms, encapsulating them one by one, separating the unchanged part from the changed part, which is actually separating the use and implementation of the algorithm. The usage of the algorithm is unchanged, and the calculated bonus is obtained according to a certain algorithm, while the implementation of the algorithm corresponds to different performance rules according to performance.16 Otolaryngology and oral cavitySupport public numbers, interact with celebrities and get the latest information.Http://bbs.a9vg.com/forum.php? Mo... & page=6 # pid52710106尹旭嘿嘿一笑，转而问道：路上还算顺利吧？尉缭回答道：还算顺利，越王你呢？越国一切可好？从尉缭的眼神之中，尹旭看出了一些不同寻常的意思，越国平定江东的事情她定然已经听说了。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.