搜索资源列表
cross-validation
- matlab交叉验证cross Validation,把样本集分为训练集和测试集,防止网络出现过拟合,提高网络的泛化能力和预测精度-cross Validation for matlab,to estimate the test accuracy,training accuray and validation accuracy of a neural network
hiden-Markov-Model
- 通过的隐马尔科夫模型的源程序,直接输入训练集(txt文档)即可。-By the hidden Markov model of the source, a non-computer science and sister debugging through the grounds, direct input training set (txt document) can, thank you sister school.
bayes_classifier_guassin-
- 贝叶斯分类器,首先生成3000个高斯分布的点,1000个点做训练集,2000个点做测试集。先运行data_generator.m自动生成两个集盒,再运行bayes_classifier.m进行分类-Bayesian classifier, the first generation 3000 Gaussian distribution of points, 1000 points to do the training set, 2000 points to do the test set. Aut
algorithm_of_BP_improve_alph_learn
- 机器学习中BP算法的一点改进,完整版,包含训练集和测试集。-Machine learning point improvement in the BP algorithm, the full version, including the training and testing sets.
BP-neural-network-predict--
- 利用MATLAB的自带工具箱函数实现了北京2009年12个月份气温、降水和气压的走势预测,且效果比较好。 BP神经网络 Bp.m BP神经网络MATLAB程序 bp_ds.xls 训练集输入 bp_nds.xls 训练集输出(目标训练集) bp_td.xls 测试集输入 bp_ntd.xls 测试集输出(目标测试集) BP神经网络预测天气值.doc 论文 -Use of MATLAB toolbox to realize the function
libsvmtest
- eclipse project导入即可使用。 本例包含用libsvm做训练分类用的完整实例。运行predict_svm.py 其中,pattern.txt是模式列表,train-c.txt,test-c.txt分别是训练集和测试集。其中svm.py和svmutil.py是来自libsvm官网3.11中的python包,经过修改之后的。 详情请看这里: 关于这个bug:http://www.tanglei.name/a-bug-in-libsvm-3.11/
T-HOMEWORK
- 用Parzen窗法或者kn近邻法估计概率密度函数,得出贝叶斯分类器,对测试样本进行测试,比较与参数估计基础上得到的分类器和分类性能的差别.2. 同时采用身高和体重数据作为特征,用Fisher线性判别方法求分类器,将该分类器应用到训练和测试样本,考察训练和测试错误情况。将训练样本和求得的决策边界画到图上,同时把以往用Bayes方法求得的分类器也画到图上,比较结果的异同。3.选择上述或以前实验的任意一种方法,用留一法在训练集上估计错误率,与在测试集上得到的错误率进行比较。-Use Parzen Wi
Bbayesiann1a
- 用贝叶斯算法解决数据挖掘中分类问题,,先用训练集进行训练,再用测试集进行测试 -Bayesian algorithm to solve the classification problem in data mining, training, first use the training set, and then the test set to test
AdaBoost
- 这是一本介绍AdaBoost算法的资料。Adaboost是一种迭代算法,其核心思想是针对同一个训练集训练不同的分类器(弱分类器),然后把这些弱分类器集合起来,构成一个更强的最终分类器-This is an introduction AdaBoost algorithm information. Adaboost is an iterative algorithm, the core idea for a training set of different classifiers (weak cl
ID31
- 用ID3算法估算打网球的天气决定因素,本代码是对天气问题的训练集建树的。-With ID3 algorithm to estimate the weather to play tennis determinants, the code is established training set of weather problems.
PCA_based-Face-Recognition-System
- 基于pca的人脸识别算法,包括matlab源代码和相关的训练集和测试集。-PCA_based Face Recognition System
ChineseSegment
- 一个完整的中文分词程序,有源码,词典,训练集。算法简洁高效,准确率高。包含了一种将标注语料和词典融合的新型分词方法。将语料分割为2:1为训练集和测试集,加上一个外部词典,准确率可以达到95 。适合入门者学习。也适合需要一个简单分词工具的应用。-A Chinese word segmentation procedures, source, dictionary, the training set. The algorithm is simple and efficient, high accura
SVM
- 首先将变压器故障的样本分成训练集和测试集两部分,然后对它们进行归一化,再用网格参数寻优得到c和g,最后进行变压器故障的预测。-SVM transformer fault diagnosis
linearfunc
- 模式识别中两种常用的线性判别函数方法。fisher函数,和MSE。train.txt是训练集。-Pattern recognition of two commonly used linear discriminant function method. fisher function, and MSE. train.txt is the training set.
TE
- 田纳西伊斯曼仿真数据,包括训练集和测试集-The Tennessee Eastman simulation data
BP
- 一个简单的神经网络实现二分类问题,里面包含代码,以及训练集和测试集的数据,可以直接用的,对初学者是不错的资源-A simple neural network to achieve the two-class problem, which contains the code, as well as training and testing data sets can be directly used, is a good resource for beginners
svmreg
- svm-分类,建模,预测等,可以分类,含训练集与测试集-svm-classification, modeling, forecasting, classification, with the training set and test set
Test
- 用libSVM实现的文本分类,包括训练集导入,训练,生成模型,测试,计算准确率和召回率-Text using libsvm to achieve the classification, including the training set import, training, generation model, test, calculate the precision and recall rate
adaboost
- daboost是一种迭代算法,其核心思想是针对同一个训练集训练不同的分类器(弱分类器),然后把这些弱分类器集合起来,构成一个更强的最终分类器 (强分类器)。-daboost is an iterative algorithm, the core idea is the same training set different classifiers (weak classifiers), and then these weak classifiers together to form a stro
FisherLDA
- Fisher线性判定函数,输入训练集及测试集,输出错误率和线性判别函数。-The Fisher Linear determine the function, enter the training set and test set, the output error rate and linear discriminant function.