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...
The nearest neighbor (NN) rule is a simple and intuitive method for solving classification problems. Originally, it uses distances to the complete training set. It performs well, ...
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Polarity lexicons have been a valuable resource for sentiment analysis and opinion mining. There are a number of such lexical resources available, but it is often suboptimal to us...
In machine learning, ensemble classifiers have been introduced for more accurate pattern classification than single classifiers. We propose a new ensemble learning method that emp...