Random over sampling works by randomly duplicating instances of the minority class until the dataset is balanced. This can be done in the following steps:
Identify the minority and majority classes in the dataset. Randomly select instances from the minority class. Duplicate these instances and add them to the dataset until the minority class has the same number of instances as the majority class.
This method can be implemented using various software tools and programming languages, such as Python and R.
