Abstract. A new classification algorithm based on combination of kernel density estimators is introduced. The method combines the estimators with different bandwidths what can be i...
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
A method is described for identification and classification of proteins encoded in large DNA sequences. Previously, an automated system was introduced for the general detection of...
Non-linear subspaces derived using kernel methods have been found to be superior compared to linear subspaces in modeling or classification tasks of several visual phenomena. Such...
In many applications, one is interested to detect certain patterns in random process signals. We consider a class of random process signals which contain sub similarities at rando...