What does "Parametric Methods" mean?

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Parametric methods are a type of statistical approach used in various fields, including machine learning. They work by making certain assumptions about the data and using parameters to define a model. These parameters help in making predictions or decisions based on new data.

In simple terms, imagine you are trying to understand how a group of people behaves based on their height and weight. A parametric method would assume that there is a relationship between these two factors and create a formula to represent this relationship. With this formula, you can then predict how a person might behave based on their height and weight.

These methods are often favored because they can be quicker and require less data to make predictions. However, they depend heavily on the assumptions made. If the real-world data does not follow these assumptions well, the predictions might not be accurate.

Parametric methods can be applied in different areas, like supervised learning, where the goal is to learn from examples and make informed decisions. This approach can help in various tasks, such as cleaning up data or finding patterns within it.