The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Enormous amount of unstructured electronic health record are invaluable for the medical research in finding the relationship between the patient's disease and the final diagnosis. How to use computer automatically dig up these information has long been a hot spot. To get the relationship between the clinical outcomes and free text writing by nurse, we developed an automatic categorization system process...
Question classification is an important part of Chinese question answering system, and the result of question classification directly affects the quality of question answering. This paper presents a new method on feature extraction for question classification. HowNet and dependency parsing are used in this new method. The classification experimental results using SVM classifier have shown that the...
Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. We focus on the sentence-level sentiment classification. On the systematically analyzing the importance and difficulties of the sentence-level sentiment classification, this paper proposes a syntax tree pruning and tree kernel-based approach to sentiment classification. In our method, the...
Support vector machine (SVM) is discussed to use for recognizing cucumber leaf diseases in this paper. Considering that it is a small number of samples, a new experimental program has been proposed which takes each spot of leaves as a sample instead of taking each leaf as a sample. In the experiments Radial Basis Function (RBF), polynomial and Sigmoid kernel function were also used to carry out comparative...
Based on radial basis function (RBF) kernel, a new self-adaptive method to optimize the least squares support vector machines (LS-SVM) parameters, the width of kernel parameter sigma and the LS-SVM regularization parameter gamma are proposed. Detailed methodology steps of this algorithm method are presented. Compared with back propagation neural networks (BPNN), various simulation experiments for...
A fault diagnosis method for analog circuits based on Support Vector Machine (SVM) and AdaBoost algorithm is developed in this paper. Firstly, output voltage signals from the test nodes are obtained from analog circuits test points and the fault feature vectors are extracted from Haar wavelet packet transform coefficients. Then, after training the AdaBoost SVM by faulty feature vectors, the SVM ensemble...
A fault diagnosis method for analog circuits based on hierarchical support vector machine (HSVM) and Dempster-Shafer (D-S) theory is developed in this paper. Firstly, output voltage signals from the test nodes are obtained from analog circuits test points and the fault feature vectors are extracted from Haar wavelet transform coefficients. Then, after training the HSVM by faulty feature vectors, the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.