Classification and Regression

Assigning objects to different classes for easier identification is a task performed frequently in many different processes. Consequently, classification algorithms can be found at the heart of a huge number of machine learning tasks. Classification can be applied to simple data like nominal, numerical, categorical and Boolean and to complex data like time series, graphs, trees etc.

The process of identifying the relationship and the effects of this relationship on the outcome of future values of objects is defined as regression. Regression helps in identifying the behavior of a variable when other variable(s) are changed in the process. Regression analysis is used for prediction and forecasting applications.

In short, when the intention is to assign objects to different categories then we use classification algorithms and when we want to predict future values then we use regression algorithms.

The different research areas we focus on with respect to classification problem are Stream mining, Text mining, Multi-label classification, Time series classification subgroup discovery, etc.