Model performance is a broad term generally used to measure how the model performs on a new dataset, usually a test dataset. The performance metrics also play the role of thresholds to decide whether the model can be put into actual decision making systems or needs improvements. In the previous chapter, we discussed some performance metrics for our continuous and discrete cases. In this chapter, we will discuss how changing the modeling process can help us improve model performance on the metrics.
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