from the full set of compatible models in classification problems. Different optimization formulations for selecting a …

This study compares the robustness of conjoint analysis versus multiple linear regression when using orthogonal data …. The explained variance (R²) by four independent variables was utilised to test the robustness of the regression analysis …

Classification arises in a wide range of applications. A variety of statistical tools have been developed for learning … classification rules from data. Understanding of their relative merits and comparisons help users to choose a proper method in … practice. This paper focuses on theoretical comparison of model-based classification methods in statistics with algorithmic …

Classification of samples into two or multi-classes is to interest of scientists in almost every field. Traditional … statistical methodology for classification does not work well when there are more variables (p) than there are samples (n) and it … is highly sensitive to outlying observations. In this study, a robust partial least squares based classification method …

simulation to validate the robustness of this composite indicator, understanding as robustness how the cities maintain the …