In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...
We describe a data structure for submatrix maximum queries in Monge matrices or Monge partial matrices, where a query specifies a contiguous submatrix of the given matrix, and it...
A measure of stability for a wide class of pattern recognition algorithms is introduced to cope with overfitting in classification problems. Based on this concept, constructive me...
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
A well-documented problem of Catmull and Clark subdivision is that, in the neighborhood of extraordinary point, the curvature is unbounded and fluctuates. In fact, since one of th...