In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
Clustering algorithms conduct a search through the space of possible organizations of a data set. In this paper, we propose two types of instance-level clustering constraints ? mu...