搜索资源列表
dataset_602132
- 经典问题TSP（旅行商算法） 蚁群算法训练集-Classic problem TSP (traveling salesman algorithm) ant colony algorithm training set
wordmark
- 通过一个已经标号词性的训练集来得到训练数据，再根据训练数据对需要进行分词的数据进行分词，采用概率最高的分词情况为最后结果。-By a label the parts of speech training set training data to get the need segmentation data based on the training data segmentation with the highest probability of segmentation for the fin
CTB
- 中文分词和词性分析通用的训练集，含POS。-Chinese word segmentation and part of speech analysis of generic training set.
license-plate-recognition-system-
- 1.先打开一幅图片然后按照顺序灰度化、二值化、灰度拉伸、车牌定位、二值化、倾斜校正、字符分割、训练神经网络、识别字符。 2.测试图像存储在当前目录的img下。 3.测试集、训练集、目标向量均存储在img下的文本文件中。-First open a picture in order graying, binarization, gray stretch, license plate location, binarization, skew correction and character s
BP
- 用C写的简单的神经网络算法，利用训练集学习并建立模型，并对测试集进行分类-Simple neural network algorithm, written in C using the training set of learning and to establish the model, and test set classification
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
nn
- 最近邻算法实现 k近邻 Z为训练集，每行一个样本，n*m labZ为与Z对应的类别，列向量 Z_T为测试集，每行一个样本，p*m labZ_T为输出结果,p*1-Nearest-neighbor algorithm
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.
Adaboost
- 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(强分类器)。-Adaboost is an iterative algorithm, its core idea is different classifications for the same training set (weak classifiers), then these weak classifiers together to form a
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
1
- 利用K-L变换进行人脸识别。首先求得待辨识图像相对于训练集平均脸的差值图像，然后求得该图像在特征脸空间中的坐标，最后采用最近邻法对图像进行归类。-KL transform for face recognition. Obtain the first image to be identified image with respect to the difference between the average face of the training set, and then obtain the
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.
C_adaboost
- adaboost算法源码，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（强分类器），通过测试可以运行-adaboost algorithm source code, Adaboost is an iterative algorithm, the core idea is the same training set for different classifiers (weak classifiers
StepclassV2
- 逐步判别分析的主函数 用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8
DecisionTree-(2)
- 决策树，根据训练集的分类结果预测测试集的分类结果，在计算机视觉和模式识别中很有用-Decision tree , test set according to the classification results of the training set, is very useful in computer vision and pattern recognition