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This paper analyses the deficiency of SVM-RFE feature selection algorithm and puts forward a new feature selection method combined with SVM-RFE and PCA. Firstly, we get the optimal feature subset through the method of cross validation based on SVM-RFE. Then, we use the PCA method to analyse the main component about optimal feature subset and get a lower-dimension and independent data sets which are...
The standard FCM is sensitive to noise deficiencies. To solve this problem, this paper presents an adaptive FCM algorithm. By way of combining cluster validity function into FCM algorithm, the adaptive identification of the cluster Numberc can be realized The experimental results show that, the improved algorithm is a robust and efficient remote sensing image ossification method
The traditional KNN algorithm for text classification has some insufficiencies, an improved KNN algorithm has been presented in this paper. By use of the clustering center vector, we put the distance of the be classified text and the text category into the similarity calculation formula, and take the ratio of the number of common features appear in two texts and the maximum number of respective features...
This paper analyses the defections of traditional support vector machine (for short SVM). According to the characteristics of grain information on the web, a multi-class classification method based on Huffman binary tree SVM (for short HBT-SVM) is presented for grain information classification. Compared with existing SVM methods, this method has higher computation efficiency. The experimental results...
This paper has proposed an improved algorithm of face detction by the combination of the respective characteristics of Adaboost algorithm and the skin color segmentation algorithm. Face candidate regions were first obtained by the means of skin color detection, which were then input as the trained Adaboost cascade classifier to get accurate and quick face location. Also, in this paper the strategy...
Spatial clustering is one of the important tasks of data mining, particle swarm optimization(PSO) algorithm has fast convergence and global optimization ability of the search features. In this paper, we present a Particle Swarm Optimization (PSO) clustering algorithm based on similarity, and improve the corresponding fitness function. Contrary to using Euclidean distance, this algorithm performs a...
Band selection is an important problem in hyperspectral image processing. In this paper, an improved adaptive band selection method is proposed to choose the best bands combination which can provide useful information, small correlation, and good property for classification. The computing process is firstly conducted by block computation to select the more valuable bands. Secondly, the Euclidean distances...
In view of the object in the image pixels and edge pixel to pixel adhesion, adhesion components due to the occurrence of the pixel gray mixed pixels, resulting in minimal differences, the traditional edge detection algorithm based on gray level because they can't distinguish adhesion part gray difference, cannot complete image edge detection problem. The image edge segmentation algorithm based on...
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