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Reporting bias: Difference between revisions
→Implications of Reporting Bias
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Data preprocessing, such as data cleaning, feature extraction, and data transformation, can also introduce reporting bias. For instance, the removal of outliers or the imputation of missing values may lead to a distortion of the underlying data distribution. | Data preprocessing, such as data cleaning, feature extraction, and data transformation, can also introduce reporting bias. For instance, the removal of outliers or the imputation of missing values may lead to a distortion of the underlying data distribution. | ||
==Implications | ==Implications== | ||
Reporting bias can have significant consequences for the performance and generalizability of machine learning models. | Reporting bias can have significant consequences for the performance and generalizability of machine learning models. | ||