数据还原核岭回归迭代超高维欧氏空间由于数据被核化后不能还原,使核方法的应用受到局限.对此,提出一种基于Multi-kernel和KRR的数据还原算法.首先,通过同类数据中已知数据进行多次核化迭代,使已知数据在超高维欧氏空间中呈线性;然后,利用已知数据对同类未知数据进行线性表示,并以Kernel ridge regression(KRR)算法进行...
kernel, filter_params=True,degree=self.degree, gamma=self.gamma, coef0=self.coef0) yPred = np.dot(H, self.Beta) return yPred 五、数据实验 这里分别采用sklearn.datasets.make_regression生成相应的多输出回归数据集,并通过归一化处理后输入至相应的MSVR模型中进行训练和测试。为了衡量多输出回归模型MS...
1 Kernel ridge regression Kernel ridge regression (KRR) 是对岭回归的一种扩展算法. 岭回归是线性最小二乘回归的惩罚形式, 其最小化代价函数为 ( ) = 1 ∑ =1 ∥ − T ∥ 2 +�∥ ∥ 2 . (1) 其中: �是确定的正则化参数, ∥.∥ 表示Frobenius 规范, 而 ∈ × . 假设存在一个矩阵 ...
Generalized multikernel correntropy based broad learning system for robust regression an emerging learning method belonging to the family of neural networks, the broad learning system (BLS) has been recently proved to be effective and effici... ZhengYunfei,WangShiyuan,ChenBadong 被引量: 0发表: 2024...
multi-class learningradial basisreproducing kernel Hilbert space (RKHSsupport vector machinesSummary: The support vector machine is known for its excellent ... Z Ji,T Hastie - Springer-Verlag 被引量: 41发表: 2002年 Support Vector Machines, Kernel Logistic Regression and Boosting multi-class learning...
摘要: Many kernel based methods for multi-task learning have been proposed, which leverage relations among tasks to enhance the overall learning accuracies. Most of the methods assume that the learning tasks share the same kernel [eg, 13], which could limit...
Furthermore, the combination of multi-level features using multi-kernel learning can further improve the classification performance. Specifically, the classification accuracy obtained by the proposed framework was 92.5 %, which was an increase of at least 5 and 17.5 % from the two-level and single...
5. Kernel learning based methods It often uses kernel representation for each view, and then incorporates different views by seeking optimal combination of multiple kernels of different views. 7. Deep learning based or network based methods
“Extreme learning machine for regression and multiclass classification” IEEE-Trans.Syst.ManCybern.:Part B, 42 (2) (2012), pp. 513-529 View in ScopusGoogle Scholar 5 X. Luo, X.H. Chang, X.J. Ban “Regression and classification using extreme learning machine based on L1-norm and L2-...
each one appropriate for each task domain, but in contrast to other support vector machine (SVM)-based proposals, learning all the parameter vectors of all individual classifiers by using the conjugate gradient method, in a global way and without the use of kernel trick, and being easily extend...