AdaBoost.M2 is a boosting algorithm designed for multiclass problems with weak base classifiers. The algorithm is designed to minimize a very loose bound on the training error. We propose two alternative boosting algorithms which also minimize bounds on performance measures. These performance measures are not as strongly connected to the expected error as the training error, but the derived bou...

each society requires a kind of management according to its structure and attainment of the goals it has been planned for. the idea of management is not new. long time ago, human had noticed the necessity of using all the facilities and leading them towards scheduled ideals. the kind of managing and leading the society depends on the cultural structure of it. so the way of management and intern...

Anesth Analg 2002; 94: 1384±8 3 Leech G. The BSE: from club to professional society. British Society of Echocardiography Newsletter, July 2003; 45: 8 4 Rimington H. Behind the Scenes. British Society of Echocardiography Newsletter, July 2003; 45: 10 5 Thys DM. Clinical competence in Echocardiography. Anesth Analg 2003; 97: 313±22 6 Pearlman AS, Gardin JM, Martin RP, et al. Guidelines for physic...

In this study, we propose a multistage neural network metalearning technique for financial time series predication. First of all, an interval sampling technique is used to generate different training subsets. Based on the different training subsets, the different neural network models with different training subsets are then trained to formulate different base models. Subsequently, to improve t...

This document summarizes a short (3 month) project exploring the use of knowledgebased training tools for Space Station payload experiments, and develop a demonstration prototype (called KB-PHaSE). The purpose of the knowledge-base is to augment existing training material with a ‘dynamic component’, whereby the user can ask questions during a training session and receive customized, situation-s...

Combining boosting and Support Vector Machine (SVM) is proved to be beneficial, but it is too complex to be feasible. This paper introduces an efficient way to boost SVM. It embraces the idea of active learning to dynamically select “important” samples into training sample set for constructing base classifiers. This method maintains a small training sample set with settled size in order to cont...

In individuals without diabetes, highintensity exercise (HIE) training may reduce (1) the characteristic postexercise rise in plasma glucose with HIE (2–4) and reduces (5,6) the marked acid-base balance perturbations (5–8). In type 1 diabetes, continuous HIE induces sustained hyperglycemia (9,10), while very brief intermittent HIE may reduce hyperglycemia (11). Acid-base disturbances during exe...