1. The impact of data quality in machine learning
The main types of error to be considered when assessing the quality of a dataset are: missing values, outliers, inconsistent values (i.e. values that do not satisfy a set of predefined constraints), and finally, duplicates, as illustrated in the table 1 .
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The impact of data quality in machine learning
Detection and correction by machine learning
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