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Model interpretation is key to understanding how predictions are made from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
To truly understand how predictions are made by a model, it is crucial to interpret the model itself. Model interpretation helps us gain insights into why the model is making certain predictions and how it is arriving at those decisions. Without this understanding, the predictions generated by the model may seem like black boxes, leaving us in the dark about the reasoning behind them. Interpreting a model involves delving into its inner workings to uncover the relationships between the input variables and the output predictions. By examining the coefficients of the model and the importance of different features, we can start to piece together the logic behind the predictions. This process not only sheds light on the decision-making process of the model but also helps us identify which features are driving the predictions and ...
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