搜索资源列表
kpca_toy
- 基于kernel pca的非线性降维算法，原文发表于神经计算杂志上，有兴趣者可以先看论文。-PCA-based kernel of nonlinear reduced dimension algorithm, the original published in the Journal of neural computation, those interested can read papers.
KDA_QR
- 基于奇异值分解的核线性判别分析（Kernel Discriminant Analysis via QR Decomposition）。 -based on the singular value decomposition of the nuclear linear discriminant analysis (Kernel Discriminant An alysis via QR Decomposition).
kfd
- 基于核的fisher判别的文献，英文，从IEEE下载下来-Kernel-based fisher discriminant literature, English, download it from the IEEE
SVMbyQuadprog
- This is a support vector machine program developed based on quadprog. Polynomial and RBF kernel are supported. Test it by executing example.m with supported data.
SupportVectorMachinesClassifierBasedonModifyingKer
- 以黎曼几何为理论依据，基于S.Amari的修正核函数思想提出了两种新的保角变换，用其对核函数进行数据依赖性改进，进一步提高支持向量机分类器泛化能力。以人工非线性分类问题 为对象进行研究，仿真实验结果表明采用新保角映射可以快速显著地改善分类器泛化性能，而且能大幅度地减少支持向量的数目。-Two novel conformal transformations were proposed based on the Riemannian geometry theory and S.Amari’sid
semisupervised_learning
- 包含8篇半监督学习方面的中文文献，关于半监督学习的中文文献并不是很多，我把我找到的一些文章贡献一下。分别为：“半监督学习综述”“有关半监督学习的问题及研究”“基于半监督学习的网络流量分析”“基于核策略的半监督学习方法”“一种基于半监督学习的多模态WEB查询精华方法”“半监督学习机制下的说话人辨认算法”“半监督学习在入侵系统中的应用”“基于半监督学习的眉毛图像分割方法”-Includes eight semi-supervised learning of Chinese literature on
Gauss-SVM
- 基于Gauss 核函数SVM分类机，使用二阶几何方法训练。-Gauss kernel function SVM classification based on machine, using the geometric method of second-order training.
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- 关于rbf神经网络实现图像分类的优化算法英文文献 源于著名期刊I-A METHOD FOR IMAGE CLASSIFICATION BASED ON KERNEL PCA
SVM
- SVM基础资料,关于核函数的分类及可支持向量机的一些资料-SVM based on information about the kernel function support vector machine classification and may some of the information
Kernel-based-robust-fuzzy-connectivity-means
- 基于连通核的鲁棒模糊C_均值聚类算法Kernel-based robust fuzzy connectivity means clustering algorithm C_-Kernel-based robust fuzzy connectivity means clustering algorithm C_
Semi-Supervised-Kernel-Based-Fuzzy
- 研究半监督学习的模糊核聚类方法用于变速箱早期故障诊断的方法。故障特征不明显、样本差异小是机械故障早期检测的 难点， 基于半监督学习的核聚类方法利用少量已知模式的样本， 结合大量未知模式的样本进行半监督学习， 得到较好的识别效果。-In this paper, motion control method of semi-closed CNC method is presented for gear-box fault early detection. The difficulty mach
fisher-and-Fuzzy-similarity
- 通过matlab语言实现Fisher分类和基于核Fisher分类的设计与实现研究和模糊相似关系直接用于分类，实现结果良好，可供大家使用，互相学习。-Fisher classifier matlab language and kernel Fisher classification-based design and realization of fuzzy similarity relations for the classification, to achieve good results fo
A-GA-based-feature-selection-and-parameters-optim
- Support Vector Machines, one of the new techniques for pattern classifi cation, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classifi cation accuracy. Feature
KPCA
- 模式识别理论中KPCA(Kernel based Principle Component Analysis)方法的推导-Kernel based Principle Component Analysis-pattern recognition
Kernel-particle-filter
- 基于核粒子滤波的视觉跟踪，采用核密度和粒子滤波结合，进行视觉图像跟踪-Nuclear density and particle filter a nuclear particle filter-based visual tracking, visual image tracking
RBF-kernel-based-on-SVM-and-RVM-
- 基于RBF核的SVM及RVM模式分析性能比较.-RBF kernel based on SVM and RVM pattern analysis performance comparison.
kernel
- 基于核的模糊C均值matlab仿真程序，功能函数是用c写的，自带图像可检验算法。-Kernel-based fuzzy C-means matlab simulation program, performance function is used to write c, comes with an image can be tested algorithms.
Kernel-Reinforcement-Learning
- 基于核函数方法的强化学习算法，用于处理连续状态空间问题或者大规模离散状态空间问题-Kernel-based reinforcement learning algorithm method for handling large-scale continuous state space problem or discrete state space problem
Shark-3.0.0
- SHARK是一种快速、模块化、功能丰富的开源C++机器学习库。它提供了线性和非线性优化的方法，基于内核的学习算法，神经网络，和其他各种机器学习技术（见下面的特征列表）。它作为一个强大的工具箱，已经在现实世界有很多应用和研究。SHARK依赖于Boost和 cmake。它兼容Windows，Solaris，MacOS X和Linux。根据GNU通用公共许可证授权许可。-SHARK is a fast, modular, feature-rich open-source C++ machine lea
wind power forecasting based on EWT-KELM
- 针对短期风电功率预测，提出一种基于经验小波变换预处理的核极限学习机组合预测方法。首先采用 EWT 对风电场实测风速数据进行自适应分解并提取具有傅立叶紧支撑的模态信号分量，针对每个分量分别构建 KELM 预测模型，最后对各个预测模型的输出进行叠加得到风速预测值并根据风电场风功特性曲线可得对应风电功率预测值。(Aiming at short-term wind power prediction, a kernel-based learning machine combination predicti