We consider the notion of prediction functions (or predictors) studied before in the context of randomness and stochasticity by Ko, and later by Ambos‐Spies and others. Predictor is a total computable function which tries to predict bits of some infinite binary sequence. The prediction error is defined as the limit of the number of incorrect answers divided by the number of answers given so far. We discuss indefiniteness of prediction errors for weak 1‐generics and show that this phenomenon affects certain c.e. sequences as well. On the other hand, a notion of optimal predictor is considered. It is shown that there is a sequence for which increasingly better predictors exist but for which no predictor is optimal.

中文翻译：

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关于不稳定和不理想的预测

我们考虑了以前在Ko和后来的Ambos-Spies等人的随机性和随机性背景下研究的预测函数（或预测变量）的概念。预测器是一种可计算的总功能，它试图预测某些无限二进制序列的位。预测误差定义为错误答案数量的极限除以到目前为止给出的答案数量。我们讨论了弱1泛型的预测误差的不确定性，并表明此现象也影响某些ce序列。另一方面，考虑了最佳预测器的概念。结果表明，存在一个序列，其存在越来越好的预测因子，但没有最优的预测因子。