Workflow 1¶

• read data
• create new class attribute
• fill in value for new class attribute based on existing attribute values (such as object, flag, etc)
• discard all attributes except magnitudes, new class attribute
• sample dataset using a combination of oversampling the minority class, undersampling the majority class to create 10 training and 10 test sets
• apply Decision tree algorithm, using 10-fold cross validation
• compute overall result
• display result
• save model
• discard training and test sets