搜索资源列表
Gamma
- gamma函数的C语言实现，用C语言来实现gamma函数，效率高，程序简洁，很好的实现了gamma函数-gamma function of the C language, using C language to realize gamma function, high efficiency, the program is simple and very good realization of the gamma function
SVMforREGRESSandclass
- SVM and contour for parameters c and gamma
gridsearch
- 这是一个libsvm grid的改进,除了可以搜索分类中的C和gamma,还可以搜索小的整数.-This file is a slight modification of grid.py of libsvm. In addition to parameters C, gamma in classification, it searches for epsilon as well. Usage: grid.py [-log2c begin,end,step] [-log2g begin
SVDD
- LIBSVM中的SVDD（Support vector data descriiption）算法，直接可用，可通过修改参数gamma和参数C来控制最后剩下的支撑矢量的数量。-The SVDD (Support vector data descriiption) algorithm in LIBSVM, directly available, and parameters by modifying the parameters of gamma C to control the last rema
gamma
- 详细介绍了一种提高数字光栅投影测量系统精度的gamma校正技术，对于学习光栅投影测量方法有很大帮助。-failed to translate
MMSE
- 本文主要介绍mmse算法及其一种改进 在最优滤波中广泛应用-The matlab files enclosed in this toolbox can be used to tabulate gain functions for log-spectral magnitude MMSE estimators under an assumed Generalized- Gamma model for the clean speech magnitude DFT coefficients.
svm-demo
- 一个svm的演示程序，能演示两类数据分类，有gui界面，不使用第三方工具箱，使用gaussian核函数，界面能设置c和gamma的参数值，最后可以得到分类情况的可视化效果。针对svm算法的研究者和用于教学演示的教师，是个不错的源码。-An svm demo program that can demonstrate two types of data classification, gui interface, do not use third-party toolbox, using gauss
light_preprocess
- 该代码是对人脸进行光照处理，先进行gamma变换，然后进行Dog双边滤波，然后进行灰度亮度的均衡。该方法能够有效提高光照变化的情况下的系统识别性能-The code is the human face of light treatment, the first for gamma conversion, and then Dog bilateral filtering, then the brightness of the gray balance. The method can effecti
CarboxySVM(Beta)
- 蛋白质位点预测的源代码，适合生物信息学初学者。-Protein gamma-carboxylation sites prediction of the source code, suitable for beginners bioinformatics.
StockSVM
- svm量化投资模型构建。预测股票的涨跌幅，以k线为基准(analyse stock "up" or 'down',based on svm model and daily k value)
python
- 该代码基于Python3,利用机器学习中支持向量机回归算法（SVR）实现对数据的拟合以及预测，可以通过调试C值和gamma值达到不同的拟合程度，具有较大的实际意义，并且该代码本人亲自调式运用，适合广大学习者使用。(This code is based on Python 3. It uses support vector machine regression algorithm (SVR) in machine learning to fit and predict the data. It c