Traditional multiple query optimization methods focus on identifying common subexpressions in sets of relational queries and on constructing their global execution plans. In this p...
: While feature selection is very difficult for high dimensional, unstructured data such as face image, it may be much easier to do if the data can be faithfully transformed into l...
Abstract. We apply a machine learning method to the occupation coding, which is a task to categorize the answers to open-ended questions regarding the respondent’s occupation. Sp...
Abstract. Bayesian spam filters, in general, compute probability estimations for tokens either without considering the email areas of occurrences except the body or treating the s...
In several contexts and domains, hierarchical agglomerative clustering (HAC) offers best-quality results, but at the price of a high complexity which reduces the size of datasets ...
The availability of microarray data has enabled several studies on the application of aggregated classifiers for molecular classification. We present a combination of classifier ag...
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Abstract. It is estimated that 20% of genes in the human genome encode for integral membrane proteins (IMPs) and some estimates are much higher. IMPs control a broad range of event...
Covariances from categorical variables are defined using a regular simplex expression for categories. The method follows the variance definition by Gini, and it gives the covaria...
We study the problem of mining frequent value sets from a large sensor network. We discuss how sensor stream data could be represented that facilitates efficient online mining and ...