Model scoring
In predictive analytics, understanding the difference between model creation and model apply or model scoring is important.
In model creation, typically large parts of prepared data from various data sources are analyzed using data mining or machine learning algorithms in order to find patterns in that data. Training models on fraud is possible if enough data exists and if the attribute combinations that were fraud in the past are known. The algorithm might detect that the probability for fraud is high whenever a credit card is used ...
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