资源列表
leaveoneout_lssvm
- 用于最小二乘支持向量机的名为\"留一法\",可用于支持向量机超参数的确定.-for least squares support vector machine called "a stay", could be used to support vector machine-determined parameters.
rcrossvalidate
- 最小二乘支持向量机中可用于确定超参数的MATLAB函数.确定参数时,需要一些时间.-least squares support vector machine can be used to determine the parameters of super - MATLAB function. Determined parameters, take some time.
denoise_kpca
- 最小二乘支持向量机岭回归函数,可以进行预测和分类-least squares support vector machine regression function Ridge, forecasts and classification
ridgeregresssvm
- 最小二乘支持向量机岭回归函数,可以进行预测和分类-least squares support vector machine regression function Ridge, forecasts and classification
robustlssvm
- 一个用于鲁棒最小二乘支持向量机的函数.可以对奇异点和非高斯分布的数据进行计算.-for a robust least squares support vector machine function. Be right singular point and the non-Gaussian distribution of data calculated.
BFS_DFS_Astar
- Implemented BFS, DFS and A* To compile this project, use the following command: g++ -o search main.cpp Then you can run it: ./search The input is loaded from a input file in.txt Here is the format of the input file: The firs
N-queen-Cplusplus
- 解国际象棋的N皇后问题的C++源代码，可用于大学计算机技术课程《算法分析》上机联系-Solutions International Chess Queen of the N C source code, University computer can be used for technical courses "algorithm analysis" on the plane link
Apriori_STL
- 使用C++STL实现的关联规则挖掘Apriori算法，代码简洁易懂。-use C STL realized Apriori association rule mining algorithm, code easy to read.
apriori_C
- 用C实现的关联规则挖掘经典算法Apriori。-C realized Mining Association Rules classical algorithm Apriori.
IBM_VC++
- IBM实验室提供的数据集生成器源码，可以数据挖掘中经常使用的关联规则数据集。-IBM laboratory data sets provided by the generator source, Data mining can be used in the association rules data sets.
SOUND1lpc
- 该函数（线性预测）主要应用于声音处理与分析，在说话人识别中有着广泛的应用！-the function (Linear Prediction) will be used in voice processing and analysis, in the words of Recognition has wide application!
annie-0.51-src
- 一个超级好用的神经网络包,包括hopfield网络等多种神经网络,在VC++环境下运行,里面有详细的说明文档-a super handy neural network packets, including hopfield neural network and other networks, VC environment in the operation, which is described in detail in documents