The long-known results of Schreier on group extensions are here raised to a categorical level by giving a factor set theory for torsors under a categorical group (G,⊗) over a small category B. We show a natural bijection between the set of equivalence classes of such torsors and [B(B),B(G,⊗)], the set of homotopy classes of continuous maps between the corresponding classifying spaces. These res...

A distance measure between objects is a key requirement for many data mining tasks like clustering, classification or outlier detection. However, for objects characterized by categorical attributes, defining meaningful distance measures is a challenging task since the values within such attributes have no inherent order, especially without additional domain knowledge. In this paper, we propose ...

This paper focuses on developing models to study influential factors on the inflation rate for a panel of available countries in the World Bank data base during 2008-2012‎. ‎For this purpose‎, Random effect log-linear and Ordinal logistic models are used for the analysis of continuous and categorical inflation rate variables‎. ‎As the original inflation rate response to variables shows an appar...

Monitoring crop areas and yields is crucial for food security and agriculture management across the world. In this paper, we mapped the biomass and yield of winter wheat using the new Project for On-Board Autonomy-Vegetation (PROBA-V) products in the North China Plain (NCP). First, the daily 100-m land surface reflectance was generated by fusing the PROBA-V 100-m and 300-m S1 products. Our resu...

This paper discusses, in a multiclass classification setting, the issue of choice so-called categorical classifier, which is procedure or criterion that transforms probabilities produced by probabilistic classifier into single category class. The standard Bayes Classifier (BC), but it has some limits with rare classes. studies performance BC versus two alternatives, are Max Difference (MDC) and...

Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the mi...