classification

Part II: Precision/Recall and Sensitivity/Specificity In the previous article on evaluation metrics for classification problems we explained that accuracy is a very useful metric and very easy to interpret. However, if the dataset we have is not balanced, it will be completely useless. We also defined what a confusion matrix Read more…

Part I: Accuracy and Confusion Matrix There are many different Machine Learning problems, and even within them, there are several ways the objective of the project and the data we have can affect how we assess our model’s performance. We will start with the evaluation metrics used in classification models. Read more…