Data Mining Methods

Developing models to forecast the class or category of a specific instance based on its characteristics, such as determining whether a client would leave, constitutes the strategy of classification.

Identifying patterns of co-occurrence between variables, such as which products are frequently bought together, is done using the association rule mining technique.

Anomaly detection is a method for spotting unusual occurrences or patterns in data that don't match the expected pattern, like spotting fraudulent transactions.

Using the clustering technique, similar instances are grouped together based on shared characteristics, for example, customers with similar purchasing habits.

Regression analysis is a method for simulating the relationship between a dependent variable and one or more independent variables. For instance, it can be used to forecast a house's price based on its size and location.

Data Mining Methods: The Top Five - DMNews