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The first limitation was that the computing environment where we built the model was slow and had limited number of machine learning algorithms. In addition, the model deployment environment limited us to a model that could be translated by a Java programmer into a single equation. Since the AAM model was developed, both the data management technology for storing and manipulating very large data sets in distributed data platforms and the availability of sophisticated machine learning algorithms designed to run in a parallel processing environment have increased rapidly.
Based on our recent experience, it reduces the variable identification, transformation and selection, modeling development, and validation time.