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.
We consider the parameter tuning problem for Gaussian-kernel support vector machines, i.e., how to set its two hyperparameters — σ (bandwidth) and C (tradeoff). Among the many methods in the literature, the majority handle this task by maximizing the cross validation accuracy over the first quadrant of the (σ, C) plane. However, they are all computationally expensive because the objective function...
With the rapid development of Internet and big explosion of text data, it has been a very significant research subject to extract valuable information from text ocean. To realize multi-classification for text sentiment, this paper promotes a RNN language model based on Long Short Term Memory (LSTM), which can get complete sequence information effectively. Compared with the traditional RNN language...
Tax audit has vital influence on improving professional quality of tax team, impartial law enforcement and construction of a clean government. View of the complexity of performance evaluation of tax audit, this paper established the performance evaluation model of tax audit to select the various influential factors via gray-relation analysis. Based on artificial neural network, it built the performance...
Heating, Ventilation and Air Conditioning(HVAC) systems perform environmental regulations to provide thermal comfort and acceptable indoor air quality. Recently optimization based Model Predictive Control (MPC) has shown promising results to improve energy efficiency of HVAC system in smart buildings. However rigorous studies on incorporating data driving comfort requirement into the MPC framework...
Game playing is a perfect domain of the study of machine learning for its simplicity that allows the researchers to focus on the learning problems themselves and ignore marginal factors. Many learning techniques derived from games have been applied successfully in other learning problems. In this paper, we introduce a Minimax Recurrence Learning algorithm to reinforce the intelligence of a game agent...
The generalization ability of neural network is an important aspect affecting its application. Meanwhile, the selection of training samples has a great impact on this ability. In order to improve the completeness of training samples, a method of samples self-learning of BP neural network based on clustering is put forward in this paper. By using the method of clustering, new samples can be collected...
Video text contains abundant high-level semantic information, which is important to video analysis, indexing and retrieval. In this paper, fuzzy support vector machine (FSVM) is applied to distinguish background and text in a video sequence. Firstly, the video frame is divided into 8×8 blocks, and we extract the gray, edge and texture feature information as the training samples. Then FSVM is used...
In this paper, we propose a novel joint topical n-gram language model that combines the semantic topic information with local constraints in the training procedure. Instead of training the n-gram language model and topic model independently, we estimate the joint probability of latent semantic topic and n-gram directly. In this procedure Latent Dirichlet allocation (LDA) is employed to compute latent...
Recognition of Chinese personal name is a difficult and challenging task in unknown words recognition. In this paper, we proposed a method of Chinese name recognition based on Support Vector Machines (SVM) and transformation-based error-driven learning. Using the transformation-based learning approach to correct the identification results of SVM. Transformation rules effectively deal with the special...
A novel spam filtering algorithm based on 2v-SVM is proposed on the basis of researching of existing spam filtering algorithms in the paper. 2v-SVM can address the difficulties that arise when the class frequencies in training data do not accurately reflect the true prior probabilities of the classes, which is more superiority than standard SVM. Experiment results show that this method can effectively...
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.