Tuesday, January 15, 2013
How to build predictive models that win competitions. (continued)
To build predictive models that are accurate and robust, it is crucial to find the input variables, or so called feature variables, that are truly predicative of the target variable. This is even more important than choosing types of predictive models. Good feature variables can greatly reduce the complexity of the modeling learning. For example, suppose we want to build a model that predicts if a pair of vectors are parallel to each other. This is illustrated in the following chart.