(Semi-)Predictive Discretization During Model Selection
نویسنده
چکیده
Data discretization is needed for various reasons. One reason is that there are many machine learning algorithms that can only be applied to discrete data. In order to use those algorithms, we need to discretize the data. We might also want to do that for solely computational reasons; some problems are easier to compute for discrete variables. Finally, if we know that our data is discrete, but we only have noisy continuous measurements, we would naturally want to discretize the data to correspond with the underlying discrete values.
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