Generative algorithms for learning classifiers use training data to separately estimate a probability model for each class. New items are classified by comparing their probabiliti...
We investigate why discretization is effective in naive-Bayes learning. We prove a theorem that identifies particular conditions under which discretization will result in naiveBay...
Abstract. Web advertisers prefer the cost-per-action (CPA) advertisement model whereby an advertiser pays a web publisher according to the actual amount of transactions, rather tha...
Abstract. We describe a new method for the exploration of evolutionary relations between protein structures. The approach is based on the ESSM algorithm for detecting structural mu...
In recent years, Denial of Service attacks have evolved into a predominant network security threat. In our previous work, we identified the necessary building blocks for an effect...