Classification is necessary and basic to scientific research. The Chinese loanword has always been a hot spot of studies on Chinese linguistics, however the range of it remained unsettled. The paper will introduce fuz...
详细信息
Classification is necessary and basic to scientific research. The Chinese loanword has always been a hot spot of studies on Chinese linguistics, however the range of it remained unsettled. The paper will introduce fuzzy set technology into the discriminant process of Chinese loanwords to compose a reliable and efficient classifier. Simulations verify the efficiency and feasibility.
During recent years, there are more and more high-quality information in the Web database. Thus, it is becoming more and more important to find the most relevant Web database to user's query. In this paper, we pro...
详细信息
There may be many fuzzy attributes in a fuzzy information system. Different fuzzy attribute has different contribution to classification. More important attributes have more contribution than the others to decision-ma...
详细信息
There may be many fuzzy attributes in a fuzzy information system. Different fuzzy attribute has different contribution to classification. More important attributes have more contribution than the others to decision-making. In this paper, based on the importance of the fuzzy condition attributes, a new method generating a fuzzy decision tree is proposed, which uses the important degree of the fuzzy condition attribute with respect to the fuzzy decision attributes to select attributes to expand the branches of a fuzzy decision tree. A comparison between the new method and fuzzy ID3 is provided. It is shown that the new method is more efficient than fuzzy ID3.
This paper proposes an image recognition method, which consists of two steps: features extraction based on wavelet transform and image recognition using artificial neural networks. More specifically, wavelet transform...
详细信息
This paper proposes an image recognition method, which consists of two steps: features extraction based on wavelet transform and image recognition using artificial neural networks. More specifically, wavelet transform is used to decompose the original image into different frequency sub-bands, then a set of features are extracted from the wavelet coefficients. The feature set as input fed into neural network for recognition. The experimental results confirmed effectiveness of the proposed approach.
Multimodal machinelearning has achieved remarkable progress in a wide range of scenarios. However, the reliability of multimodal learning remains largely unexplored. In this paper, through extensive empirical studies...
详细信息
The imbalanced data classification problem has aroused lots of concerns from both academia and industry since data imbalance is a widespread phenomenon in many real-world scenarios. Although this problem has been well...
详细信息
A new method, multi-class fuzzy support vector machine of dismissing margin (DMFSVM) based on class-center, is proposed aiming at the outliers and noises which appear in the large quantity samples. Compared with tradi...
详细信息
A new method, multi-class fuzzy support vector machine of dismissing margin (DMFSVM) based on class-center, is proposed aiming at the outliers and noises which appear in the large quantity samples. Compared with traditional SVM, this new method eliminates the sensibility of optimal separating hyperplane. It weeds out some sample points which may not be support vectors. And this will be able to decrease the corresponding optimization problem dimension, reduce the memory and the amount of computation, but increase the training speed. At the same time, the new algorithm adopts fuzzy membership function of decreasing Semi-Cauchy type. The advantages are through regulating parameters of fuzzy factor suitably according to the specific circumstances to make the fuzzy factor of isolated points smaller and the fuzzy factor of support vectors larger relatively. So this method can fit the characteristics of fuzzy classification well.
Rough set approach based on dominance- equivalence relation can be used to handle classification problems with preference ordered conditional attributes. It firstly extracts the most important information to the decis...
详细信息
ISBN:
(纸本)9781538652152
Rough set approach based on dominance- equivalence relation can be used to handle classification problems with preference ordered conditional attributes. It firstly extracts the most important information to the decisions, and then approximates target concepts and finally form the decision-making knowledge. In this paper, we study the issue of updating knowledge in classification problems under dynamic environments. When some samples are inserted or deleted, the update principle of dominating sets is given and the approximate reduction algorithm based on sample selection is developed. The proposed method only needs to individually consider the impact of changing samples on knowledge reduction, and therefore it can obviously reduce the storage space. More importantly, since it can utilize previous calculation results, the time cost of subsequent calculations is thus significantly reduced. Ten UCI data sets are selected in our experiments. The results show the effectiveness and efficiency of the proposed method.
Patch-level features are essential for achieving good performance in computer vision tasks. Besides well-known pre-defined patch-level descriptors such as scaleinvariant feature transform (SIFT) and histogram of orien...
详细信息
Generative adversarial networks (GANs) has received wide attention in the machinelearning field because it can generate real-like data by estimating real data probability distribution. GANs has been successfully appl...
详细信息
Generative adversarial networks (GANs) has received wide attention in the machinelearning field because it can generate real-like data by estimating real data probability distribution. GANs has been successfully applied to many fields such as computer vision, pattern recognition, natural language processing and so on. By now many kinds of extended models of GANs have been proposed and investigated by different researchers from different viewpoints. Although there are a few review papers on the extended models of GANs in the literature, some remarkable extensions of GANs published in the recent years are not included in these surveys. This paper attempts to provide the potential readers with a recent advance on GANs by surveying its twelve representative variants. Furthermore, we also present the lineage of the extended models of GANs. This paper can provide researchers engaged in related works with very valuable help.
暂无评论