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- W2789383625 abstract "Removal of outliers is the simplest type of data filtering. Even though sometimes outliers should be kept in the data set as part of the analysis, such as in the case of modeling of credit risk, fraud, and other rare events, in most of the cases, they represent unnecessary information and should be removed. Unnecessary outliers are noise in the data and mostly can reduce the predictability of the model. This tutorial shows an automatic and manual way to remove outliers." @default.
- W2789383625 created "2018-03-29" @default.
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- W2789383625 date "2018-01-01" @default.
- W2789383625 modified "2023-09-25" @default.
- W2789383625 title "Data Prep 2-3: Outlier Handling" @default.
- W2789383625 doi "https://doi.org/10.1016/b978-0-12-416632-5.00034-7" @default.
- W2789383625 hasPublicationYear "2018" @default.
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