…tandard machine learning approaches at these problems, such as linear regression or random forests, often the model will overfit the samples with the highest values in order to reduce metrics such as mean absolute error. However, what you may actually want is to treat the samples with similar weighting, and to use an e…
…ne of the problems that I’ve encountered a few times when working with financial data is that often you need to build predictive models where the output can have a wide range of values, across different orders of magnitude. For example, this can happen when predicting housing prices, where some homes are valued at $100k a…