The RMS error is a measure of the difference between predicted and actual values, and it's essential to minimize it to improve the accuracy of predictions. In this article, we'll discuss how to reduce the RMS error value in regression analysis and predictions by focusing on feature engineering and model selection.

If you get an RMS error, read the message to understand the issue. For example, if you want to buy 1000 shares with 20000, but the RMS error states that the required Amount required is 20156, so simply you can reduce them, now your order will get easily placed.

RMS rejections happen because due to some reason or the other, the order entered is rejected by the RMS System of SAMCO. Thus the order is stopped at the broker level itself and is not sent to the exchange for trading.

The error and complementary error functions occur, for example, in solutions of the heat equation when boundary conditions are given by the Heaviside step function. The error function and its approximations can be used to estimate results that hold with high probability or with low probability.

layer norm：减去样本的均值，除以样本的方差，使得整体样本不要太分散。 RMS（root mean square） Norm：去除了减去均值的操作，也就是没有去中心化的操作，只有缩放的操作。RMSnorm就是均值为0的layer norm。 L-…