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svm_v0.55beta
- 最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, \"The Nature of Statistical Learning Theory\", Springer-Verl
Inertiadevicefaultpredictionbasedonwavelet
- ：为了提高最小二乘支持向量回归机的性能，将Morlet小波核函数引入其中，形成了最小二乘小波支 持向量回归机模型。利用待优化的参数重构模型的目标函数和约束条件，并在此基础上通过遗传算法进行参数 选择，从而提高了该模型的泛化能力。将最小二乘小波支持向量回归机应用于导弹陀螺仪的漂移趋势预测，仿真 实验结果表明了该方法的有效性和可行性，因此可以为陀螺仪的故障预报、可靠性辅助决策提供依据。-To improve the ability of least square support vect
mvkernelsmoothing
- 多维核平滑回归，对于存在数据点缺失或含噪声的情况，具有较好的鲁棒性。-Multi-dimensional kernel smoothing regression, data points for the existence of the case of missing or noisy, and has good robustness.
elm_kernel
- 不同的核函数的elm,既包括分类算法，也包括回归，十分的全面，运行无错误！-Elm different kernel functions, including both classification algorithms, including regression, very comprehensive and error-free operation!
libORF-master
- 针对各种机器学习，深度学习领域的一个matlab工具包-A machine learning library focused on deep learning.Following algorithms and models are provided along with some static utility classes: - Naive Bayes, Linear Regression, Logistic Regression, Softmax Regression, Linear S
2SVR
- 支持向量机回归的ｍａｔｌａｂ版本，里面包含高斯核函数等一系列常用的核函数。(Support vector regression matlab version, which contains the Gauss kernel function and a series of commonly used kernel functions.)
MatlabRegressionCode
- lssvm回归预测分析，用各种核函数进行参数调优过程，使获得最佳的预测结果。(Lssvm regression prediction analysis, with a variety of kernel functions for parameter tuning process, so that the best predictions.)
KRR
- 核岭回归算法 输入数据集(需要分开存放训练集和测试集) 利用4重交叉验证法调参 最后输出分类准确率(Kernel ridge regression algorithm Input data set (training set and test set need to be stored separately) Parameter adjustment by 4-fold cross validation Final output classification accuracy)