We show that all consistent learning methods—i.e., that asymptotically achieve the lowest possible expected loss for any distribution on (X,Y )—are necessarily localizable, by which we mean that they do not significantly change their response at a particular point when we show them only the part of the training set that is close to that point. This is true in particular for methods that appear ...

An interleaved integration of the planning and scheduling process is presented with the idea of including soft temporal constraints in a partial order planner that is being used as the core module of an intelligent decision support system for the design forest fire fighting plans. These soft temporal constraints have been defined through fuzzy sets. This representation allows us a flexible repr...

The decomposition method is currently one of the major methods for solving support vector machines (SVM). Its convergence properties have not been fully understood. The general asymptotic convergence was first proposed by Chang et al. However, their working set selection does not coincide with existing implementation. A later breakthrough by Keerthi and Gilbert (2000, 2002) proved the convergen...

This paper is aimed at describing a framework to implement Multi-Class Support Vector Machine (MCSVM)-based motion intention recognition. To this end, we primarily constructed a wearable exoskeleton robot of lower body which is employed as an experimentation platform to test the MCSVM-based motion intention recognition. Having disclosed prototype development and MCSVM, experimental results of m...

In this paper, a support vector machines (SVMs) based method is proposed for content-based audio classification and retrieval. Given a feature set, which in this work is composed of perceptual and cepstral feature, optimal class boundaries between classes are learned from training data by using SVMs. Matches are ranked by using distances from boundaries. Experiments are presented to compare var...

In this paper, a proposed Group Decision Support Systems model based on Rough Set is presented. The model improves decision making process by using rough set as a tool for knowledge discovery on decision support system, where the same feature may evaluate by one decision maker as good and by another one as medium, in this case inconsistent will appear in decision problem. To cope with this prob...

For the engine fault diagnosis in real problems, the number of samples available are limited, and the progress of research on the theory of the most limited to assume that the data samples, so that the network training data examples, in engineering applications has been slow, in this paper, the application of support vector machine in fault diagnosis of engine, the segmentation of the training ...

In this work, we developed classifiers to distinguish between four ovarian tumor types using Bayesian least squares support vector machines (LS-SVMs) and kernel logistic regression. Input selection using rank-one updates for LS-SVMs performed better than automatic relevance determination. Evaluation on an independent test set showed good performance of the classifiers to distinguish between all...

This paper studies financial crisis of listed companies in China Manufacture Industry, and selects 181 companies with financial crisis and 181 normal companies as its research samples, and its research is based on financial indexes three years before the financial crisis happens. Firstly the method of principle component analysis is used to abstract useful information from the training data. Se...

Relational database management systems manages the tables with predefined indexes. In RDBMS indexes are created on the basis of attribute values. The Imine indexing scheme is used to index item sets in relational databases. The index creation is performed with out any constraints. IMine provides a complete representation of the original database. The Imine indexing scheme reduces the input/outp...