In this paper, a new kernel PCA, referred to as the direct kernel PCA (DKPCA), is proposed for face recognition, which explicitly maps an input image nonlinearly into a feature space and then computes the principal components directly in the mapped space. Therefore, this method considers the...
X = pca.transform(data_train)# Generate grid along first two principal componentsmultiples = np.arange(-2,2,0.1)# steps along first componentfirst = multiples[:, np.newaxis] * pca.components_[0, :]# steps along second componentsecond = multiples[:, np.newaxis] * pca.components_[1, :]...
In this paper, Principal Component Analysis (PCA) is used for reducing features of breast cancer, lung cancer and heart disease data sets and an empirical comparison of kernel selection using PSO for SVM is used to achieve better performance. This paper focused on SVM trained using linear, ...
人将主元分析算法(PCA)与RBF网络结合来建立聚酯粘度的软测量模型【4】。 余佩菲将核主元分析算法(KPCA)与RBF网络结合建立了阿维菌素发酵过程的 软测量模型【51。 目前神经网络里除了BP网络和RBF网络在软测量中广泛应用之外,像递 归网络、过程神经网络等在软测量中也有应用,在文献中也有相关的报道。如 ...
Face Recognition Using Kernel PCA and Hierarchical RBF Network This paper proposes a new face recognition approach by using kernel principal component analysis (KPCA) and hierarchical radial basis function (HRBF) netwo... Z Jin,L Yang,Y Chen - International Conference on Computer Information Systems...
基于核PCA与在线支持向量机的电子鼻气体分类研究 在线支持向量机(Online-SVM)RBF神经网络通过电子鼻系统获取的数据具有维数高,非线性变化等特点,不利于后续算法的识别或分类.因此,提出了基于核主元分析(KPCA)与... 余炜,万代立,周娅,... - 《计算机应用与软件》 被引量: 1发表: 2015年 ...
Our results on KDDCUP99 shows our proposed method have better performance related to other feature transformation methods such as LDA, PCA, Kernel Discriminant Analysis (KDA) and Local Linear Embedding (LLE).doi:10.11591/ijins.v1i1.339Saeid Asgari Taghanaki...
After the screening, the sample features are selected and the PCA is used. A method is used to reduce the dimension; and the first training of the classifier is carried out afterwards. Next, three cross experiments of 2-fold, 5-fold, and 10-fold are carried out, and the results are ...
Classifier for CIFAR-10. Grayscaling, HOG, PCA, and RBF SVM. 62% test accuracy. Walkthrough on YouTube:https://youtu.be/gmTweV0eHhk svmpcacifar10hogrbf UpdatedNov 24, 2024 Jupyter Notebook Spatial interpolation python package interpolationgeostatisticskrigingrbf ...
Keywords gas outburst, soft sensor model, kernel function, principal component analysis, RBF NN 1 1) 2) 1 1 1 2 401331 L KPCA RBF E (PCA) KPCA RBF RBF 8 8 RBF 1 ( E 8 8 8 L 8 L KPCA PCA KPCA PCA 3&$ >@ >@ L L 978-1-4244-2114-5/08/$25.00 ©...