Feature construction is essential for solving many complex learning problems. Unfortunately, the construction of features usually implies searching a very large space of possibilities and is often computationally demanding. In this work, we propose a case based approach to feature construction. Learning tasks are stored together with a corresponding set of constructed features in a case base an...

In this report we show that the-tube size in Support Vector Machine (SVM) for regression is 2= p 1 + jjwjj 2. By using this result we show that, in the case all the data points are inside the-tube, minimizing jjwjj 2 in SVM for regression is equivalent to maximizing the distance between the approximating hyperplane and the farest points in the training set. Moreover, in the most general setting...