资源列表
naivebaysianclassify
- 分类源代码，为研究神经网络的同学提供帮助-classification source for the study of neural networks to help provide students
SVM-feature-optimization_GridSearch
- 在支持向量机做分类的参数优化过程中采用GridSearch方法进行参数优化，优化后可以得到较好的分类效果。-GridSearch method using SVM classification parameters to do the optimization process parameter optimization, you can get a better classification results after optimization.
neural-network-classification
- 使用分类算法中的神经网络算法进行数据分类，实验表明算法可以得到较好的分类效果。-Classification algorithm using neural network algorithm for data classification, experiments show that the algorithm can get better classification results.
SVM-regression-forecasting
- 支持向量机除了可以进行分类预测还可以进行回归预测，源代码为使用支持向量进行回归预测。-In addition to SVM classification can also be predicted regression prediction, the source code for the use of support vector regression to predict.
SVM-classification-forecasting
- 使用支持向量机进行数据分类的预测，文件给出了预测程序的源代码。-SVM prediction using data classification, document gives a prediction program source code.
SVM-feature-optimization_GA
- 使用SVM进行分类过程中的参数优化问题，通过优化可以达到较好的分类效果。-Using SVM classification process parameter optimization problem by optimization can achieve better classification results.
GACODE
- 遗传算法的标准程式,可以通过简单修改,并增加自己的内容
GA实数编码遗传算法程序
- 实数编码遗传算法程序，可用于模型参数辨识，也有其它的用途
hmmviterbi
- 计算隐马尔可夫模型序列的最可能的状态路径-Hidden Markov model to calculate the most likely state sequence path
hmmtrain
- 隐马尔可夫模型参数的极大似然估计,用来求解HMM的第三个问题-HMM maximum likelihood parameter estimates used to solve the third problem HMM
hmmgenerate
- 由一个隐马尔可夫模型产生一个观测值序列和一个状态序列-Consists of a hidden Markov model to generate a sequence of observations and a state sequence
hmmestimate
- 给定观测序列和状态序列下估计HMM模型的参数-Given the HMM parameters under observation sequence and state sequence estimation