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Challenges exist in predictive modeling from "summary" of Predictive Analytics by Eric Siegel
Predictive modeling is an incredibly powerful tool, allowing organizations to make informed decisions and predict future outcomes based on historical data. However, it is important to recognize that challenges exist in this process that can impact the accuracy and effectiveness of predictive models. One of the main challenges in predictive modeling is the quality of the data being used. Data can be incomplete, inaccurate, or biased, which can lead to misleading results. It is essential to carefully clean and preprocess data before building a predictive model to ensure its reliability and validity. Another challenge is the complexity of the models themselves. As models become more sophisticated, they can become harder to interpret and explain. This lack of transparency can lead to difficulties in understanding how predictions are being made and can make it challenging to gain buy-in from stakeholders. Furthermore, ove...
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