ATTRIBUTE SELECTION FOR MODELING

Modelling a target attribute by other attributes in the data is perhap s the most traditional data mining task. When there are many attribute s in the data, one needs to know which of the attribute(s) are relevan t for modelling the target, either as a group or the one feature that is most appropriate to select within the model construction process in progress. There are many approaches for selecting the attribute(s) in machine learning. We examine various important concepts and approache s that are used for this purpose and contrast their strengths. Discret ization of numeric attributes is also discussed for its use is prevale nt in many modelling techniques.