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Anomalies are often considered bad because they represent deviations from expected behavior, which can indicate underlying problems or inefficiencies. In various contexts, such as finance, manufacturing, or data analysis, anomalies may signal fraud, errors, or operational failures that can lead to significant losses or risks. Additionally, they complicate decision-making and can undermine the reliability of models and forecasts, making it difficult to achieve consistent outcomes. Therefore, identifying and addressing anomalies is crucial for maintaining stability and effectiveness in systems and processes.

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2mo ago

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