Transmembrane proteins play an important role in cellular energy production, signal transmission, metabolism. Existing machine learning methods are difficult to model the global correlation of the membrane protein seq...
详细信息
Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The res...
详细信息
ISBN:
(纸本)9781509034857
Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.
This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as...
详细信息
ISBN:
(纸本)9781479919611
This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.
With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and tex...
详细信息
Discriminant neighborhood embedding (DNE) algorithm is one of supervised linear dimensionality reduction methods. Its nonlinear version kernel discriminant neighborhood embedding (KDNE) is expected to behave well on c...
详细信息
Discriminant neighborhood embedding (DNE) algorithm is one of supervised linear dimensionality reduction methods. Its nonlinear version kernel discriminant neighborhood embedding (KDNE) is expected to behave well on classification tasks. However, since KDNE constructs an adjacent graph in the original space, the adjacency graph could not represent the adjacent information in the kernel mapping space. By introducing hidden space, this paper proposes a novel nonlinear method for DNE, called hidden space discriminant neighborhood embedding (HDNE). This algorithm first maps the data in the original space into a high dimensional hidden space by a set of nonlinear hidden functions, and then builds an adjacent graph incorporating neighborhood information of the dataset in the hidden space. Finally, DNE is used to find a transformation matrix which would map the data in the hidden space to a low-dimensional subspace. The proposed method is applied to ORL face and MNIST handwritten digit databases. Experimental results show that the proposed method is efficiency for classification tasks.
In general,Chinese event factuality is determined by the specific vocabularies and syntactic structures of *** Chinese event factuality corpus is to annotate these specific vocabularies and syntactic *** these informa...
详细信息
In general,Chinese event factuality is determined by the specific vocabularies and syntactic structures of *** Chinese event factuality corpus is to annotate these specific vocabularies and syntactic *** these information is raw and complex,it will result in high computation complexity and low correct rate if we use these information to compute factuality *** paper proposes a 3D representation of Chinese event factuality based on the annotated factual information in a Chinese event factuality *** also presents the transformation rules between the factual information and 3D representation and those between the 3D representation and event *** experimental results demonstrate the effectiveness of our 3D representation.
Fountain code is a class of graph-based linear erasure codes, which can effectively solve the problems such as network congestion and feedback cracking for its characteristics of rateless and can resume when interrupt...
详细信息
ISBN:
(纸本)9781479973408
Fountain code is a class of graph-based linear erasure codes, which can effectively solve the problems such as network congestion and feedback cracking for its characteristics of rateless and can resume when interrupted, and has a lower complexity of encoding and decoding. However, there are still some problems in the process of encoding and decoding, including the degree distribution structure may be destroyed, parameters of the generating matrix are not fixed, and it cannot recover source datas from the remaining encoded packets with no degree one. So, the basic theory of fountain codes from three aspects are introduced in this paper, i.e., degree distribution, encoding and decoding principles. Therefore the improved algorithms according to the above three aspects are presented. Simulation results show that the proposed algorithm is more efficient than the previous one.
Online Social Networks (OSNs) are becoming popular and attracting lots of participants. In OSN based e-commerce platforms, a buyer’s review of a product is one of the most important factors for other buyers’ decisio...
详细信息
With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and tex...
详细信息
暂无评论