Machine Learning Concept 70 : A-B / A-A-B Testing.
In order to know how powerful the machine learning model is in numerical value we can do by practically applying all the models to the database or else we can do A-B testing & A-A-B testing.
A-B / A-A-B Testing:
A/B testing is a statistical hypothesis testing method that is commonly used in machine learning and data-driven decision-making. It is a technique used to determine whether a particular treatment or intervention has an effect on the outcome of interest, by randomly assigning participants to one of two or more groups and comparing their outcomes.
In an A/B test, two groups are formed, one group (A) is the control group, which receives the existing or standard treatment, while the other group (B) receives the new or experimental treatment. The goal is to compare the outcomes between the two groups and determine whether the new treatment is better, worse, or equivalent to the existing treatment.
A/A/B testing, on the other hand, is a variant of A/B testing, where two identical control groups are used in addition to the experimental group. This method helps to ensure the statistical validity of…
