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Heart disease classification is one of the most important topics in clinical decision support systems (CDSS). However, the performance of classification is greatly affected by feature selection. Canonical correlation analysis (CCA) is a popular method to extract effective features from two relevant data sets. In this paper, we employ discriminant minimum class locality preserving canonical correlation...
With the development of machine learning techniques, artificial intelligence applications in medicine are becoming hot topic in health information systems. In this research, we construct a new basic heart failure disease database which contains 1715 patients and 400 features. Then, we propose a new machine learning method called Polynomial Smooth Support Vector Machine(PSSVM) to help doctors diagnose...
Incorporating the k-nearest neighbor information and lazy random walks on graph, this paper presents a supervised classifier, namely supervised lazy random walk (SLRW) classifier. First, a partially labeled graph is built over the input data, where the edge weight represents the locally scaled pair wise similarity based on the k-nearest neighbors. And then the SLRW classifier is trained with lazy...
An intelligent gas sensor is developed which used for gas concentration measurement. This device applies ARM7 kernel as the Microcontroller to measure the thin film's resistance. After calibrating the gas concentration with component's resistance, the sensor displays the gas concentration. To reduce adjunctive error which result from temperature drift, and improve the precise of the sensor, a compensational...
Nonlinear multi-classification has been a popular task in machine learning recently. In this paper, we propose a nonlinear multi-classification algorithm named Supervised Spectral Space Classifier (S3C), S3C integrates the discriminative information into the spectral graph mapping and transforms the input data into the low-dimensional supervised spectral space. S3C not only enables researchers to...
Facial expression recognition has received more and more attentions during the last two decades. A variety of recognition techniques have been applied in various applications. In this paper, a novel expression recognition technique is proposed based on a state-of-the-art classifier called minimax probability machine (MPM). After introducing some technical details of preprocessing and feature extraction,...
Many of characteristics of support vector machine (SVM) are determined by the type of kernels used. Traditional kernels such as polynomial kernel and radial basis function kernel have many limitations. It is valuable to investigate the problem of whether a better performance could be obtained if we construct a scaling kernel by using the scaling function. This paper presents a way for building a wavelet-based...
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