binary classification

Binary classification is a type of Classification task that involves predicting one of two possible classes or outcomes. It is used in scenarios where the goal is to categorize data into two distinct groups, such as spam vs. not spam in email filtering or disease vs. no disease in medical diagnosis.

Use pycaret for binary classification. This can use many models and compare them. Can do

• ROC and AUC
• Confusion matrix
• Feature importance
• Model evaluation - must do in ipynb

In ML_Tools see:

• https://github.com/rhyslwells/ML_Tools/blob/main/Explorations/Build/Classifiers/Classification/Tutorial-BinaryClassification.ipynb