Machine learning models are particularly good at determining which of many possible variables will work best and recognizing that some things don’t matter and others, perhaps surprisingly, do. Now, an analyst’s intuition and hypotheses are less important. In this way, machine learning enables predictions based on unanticipated correlations, including that housing prices in Las Vegas, Phoenix, and Miami might move together.
