Machine Learning Fundamentals Sensitivity And Specificity
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Roc (receiver operator characteristic) graphs and auc (the area under the curve), are useful for consolidating information from a ton of confusion matric.
One of the fundamental concepts in machine learning is confusion matrix. This video walks you through cost complexity pruning, aka weakest link. In this statquest we talk about sensitivity and specificity to key concepts for evaluating machine learning methods.
Check out the course here. Combined with cross validation, it's how we decide which method. These make it easier choose which m.
This video is part of an online course, model building and validation. Pruning regression trees is one the most important ways we can prevent them from overfitting training data. In this video we talk about sensitivity and specificity is used to determine the proportion of actual positive cases, which got predicted corre.
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