background: the two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. the objective of the present study was to classify the different countries based on the death rates from sex specific cancers. methods : in this cross-sectional study, we used dataset regarding death rate from breast, cervical, uterine, and ovarian cancers in 190 countries worldwide repo...

We developed a new semi-supervised EM-like algorithm that is given the set of objects present in eachtraining image, but does not know which regions correspond to which objects. We have tested thealgorithm on a dataset of 860 hand-labeled color images using only color and texture features, and theresults show that our EM variant is able to break the symmetry in the initial solution. We compared...

This paper presents a system of data decomposition and spatial mixture modeling for part based models. Recently, many enhanced part based models (with e.g., multiple features, more components or parts) have been proposed. Nevertheless, those enhanced models bring high computation cost together with the risk of over-fitting. To tackle this problem, we propose a data decomposition method for part...

where K is the (fixed) number of mixture component, π is a vector of mixing weights, and p(x|k) are the densities for each component. We consider some examples below. 2 Gaussian mixture models Consider the dataset of height and weight in Figure 1. It is clear that there are two subpopulations in this data set, and in this case they are easy to interpret: one represents males and the other femal...

Consider the task of summarizing the data in Figure 1. A common technique for performing this task is to use a statistical model known as a mixture model. Relative to many other models for estimating densities, mixture models have a number of advantages. First, mixture models can summarize data that contain multiple modes. In this sense, they are more powerful than distributions from the expone...