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John asked if there were any obvious "turnkey" machine learning algorithms to try on the El Nino problem that haven't been suggested yet. In the course of thinking about that, I became aware that I haven't read all of the posts on the forum over the past 6 months. Has there been any thought about if one could come up with a continuous statistic that measures how much of an El Nino is/isn't occurring? (eg, a severe El Nino, a mild El Nino, behaviour that's close to an El Nino but doesn't cross the threshold, nothing like an El Nino, etc.) Complete fidelity isn't important, it's just that some "regression type" machine learning techniques perform a lot worse when you represent very different examples of outputs with class labels 0 and 1 rather than a more continuous measure.