Evaluating machine learning models

In this section, we will discuss how to evaluate a machine learning model because you should always evaluate a model to determine if it is ready to perform well consistently, predicting the target for new and future data. Obviously future data might have many unknown target values. Therefore, you need to check performance-related metrics such as the accuracy metric of the ML model on the data. In this regard, you need to provide a dataset containing scores generated from a trained model and then evaluate the model to compute a set of industry-standard evaluation metrics.

To evaluate a model appropriately, you need to present a sample of data that has been labeled with the target and this data will be used as the ...

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