Comparison of Variable Importance Measures in Tree-based Classification

Object-Based Classification of UltraCamD Imagery for Identification of Tree Species in the Mixed Planted Forest

This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...

A Classification Scheme for Importance Measures

Importance measures are playing a valuable role in the transitioning strategy to risk-informed regulation. In this report the basic mathematical elements, the F(.) parameters, used in defining importance measures will be further analyzed to bring their properties into the open. The F(.) parameters are used throughout this paper to define the six importance measures used in the SAPHIRE code, to ...

comparison of catalytic activity of heteropoly compounds in the synthesis of bis(indolyl)alkanes.

heteropoly acids (hpa) and their salts have advantages as catalysts which make them both economically and environmentally attractive, strong br?nsted acidity, exhibiting fast reversible multi-electron redox transformations under rather mild conditions, very high solubility in polar solvents, fairly high thermal stability in the solid states, and efficient oxidizing ability, so that they are imp...

Variable Importance in Nonlinear Kernels (VINK): Classification of Digitized Histopathology

Quantitative histomorphometry is the process of modeling appearance of disease morphology on digitized histopathology images via image-based features (e.g., texture, graphs). Due to the curse of dimensionality, building classifiers with large numbers of features requires feature selection (which may require a large training set) or dimensionality reduction (DR). DR methods map the original high...

Robust Measures of Variable Importance for Multivariate Group Designs