In order to improve the ability of gradual learning on the training set gotten in batches of Naive Bayesian classifier, an incremental Naïve Bayesian learning algorithm is improved with the research on the existing incremental Naïve Bayesian learning algorithms. Aiming at the problems with the existing incremental amending sample selection strategy, the paper introduced the concept of sample Cl...

MOTIVATION We recently introduced a multivariate approach that selects a subset of predictive genes jointly for sample classification based on expression data. We tested the algorithm on colon and leukemia data sets. As an extension to our earlier work, we systematically examine the sensitivity, reproducibility and stability of gene selection/sample classification to the choice of parameters of...

The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in an acceptable classification accuracy. Therefore, a good feature selection method based on the number of features investigated for sample classification is needed in order to speed u...

Classification trees are a popular statistical tool with multiple applications. Recent advancements of traditional classification trees, such as the approach of classification trees based on imprecise probabilities by Abellán and Moral (2004), effectively address their tendency to overfitting. However, another flaw inherent in traditional classification trees is not eliminated by the imprecise ...

this study examins effects of trade liberalization on the wage inequality across industries and between genders within these industries by utilizing the data of micro-level households’ income and expenditures surveys and trade statistics over 2001-2011. the analysis is carried based on the heckscher–ohlin’s theory in international trade and baker’s taste discrimination theory at firms. we use q...

This paper studies the problem of building multiclass classifiers for tissue classification based on gene expression. The recent development of microarray technologies has enabled biologists to quantify gene expression of tens of thousands of genes in a single experiment. Biologists have begun collecting gene expression for a large number of samples. One of the urgent issues in the use of micro...

Classification trees are a popular statistical tool with multiple applications. Recent advancements of traditional classification trees, such as the approach of classification trees based on imprecise probabilities by Abellán and Moral (2005), effectively address their tendency to overfitting. However, another flaw inherent in traditional classification trees is not eliminated by the imprecise ...