VALIS is an effective and robust classification algorithm with a focus on understandability. Its name stems from Vote-ALlocating Immune System, as it evolves a population of artificial antibodies that can bind to the input data, and performs classification through a voting process. In the beginning of the training, VALIS generates a set of random candidate antibodies; at each iteration, it selects the most useful ones to produce new candidates, while the least, are discarded; the process is iterated until a user-defined stopping condition. The paradigm allows the user to get a visual insight of the learning dynamics, helping to supervise the process, pinpoint problems, and tweak feature engineering. VALIS is tested against nine state-of-the-art classification algorithms on six popular benchmark problems; results demonstrate that it is competitive with well-established black-box techniques, and superior in specific corner cases.

中文翻译：

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VALIS：一种进化分类算法

VALIS 是一种有效且稳健的分类算法，重点是可理解性。它的名字来源于投票分配免疫系统，因为它进化出一群可以与输入数据结合的人工抗体，并通过投票过程进行分类。在训练开始时，VALIS 生成一组随机的候选抗体；在每次迭代中，它选择最有用的来产生新的候选者，而最少的被丢弃；该过程被迭代，直到用户定义的停止条件。该范式允许用户对学习动态有一个直观的了解，有助于监督过程、查明问题和调整特征工程。VALIS 在六个流行的基准问题上针对九种最先进的分类算法进行了测试；