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 negative credit action


Avoiding Human Error When Building Artificial Intelligence

#artificialintelligence

Many real-life databases contain missing values. Yet many popular algorithms and statistical models do not accept data rows containing missing values. Some libraries drop these data rows with little warning. Without those data rows, a model is likely to make biased predictions. For example, a majority of the rows in the Lending Club data have never had a negative credit action and therefore contain a missing value.