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MATLAB实现鸢尾花数据集分类
- 基于BP算法的鸢尾花数据集分类，在MATLAB平台下编程实现BP算法，可计算识别率。(Based on the BP algorithm, iris data set is classified. Under the MATLAB platform, the BP algorithm is programmed and the recognition rate can be calculated.)
Span_H_Alpha分类
- 参照论文《基于SPAN／H／alpha／A和复Wishart分割的全极化SAR数据的非监督分类算法研究》(Referenced research on unsupervised classification algorithm of fully polarimetric SAR data based on SPAN / H / alpha / A and complex Wishart segmentation)
分类器评估及交叉验证_代码
- 内有鸢尾花数据的5折交叉验证实验代码，采用的分类器是贝叶斯分类器。(There is a 5-fold cross-validation experiment code for the iris data, and the classifier used is a Bayesian classifier.)
kmeans图像分类
- 利用简单kmeans聚类算法，对不同图片进行分类，图片内容包括人像，风景，建筑，动物，植物等，平台是matlab。(The simple k - means clustering algorithm is used to classify different pictures. the picture content includes portrait, scenery, architecture, objects, plants, e
mnist分类
- mnist分类，python，tensorflow，深层神经网络(MNIST classification, python, tensorflow, deep neural network)
matlab贝叶斯分类(1)-简单样本集
- 利用matlab实现贝叶斯分类，采取“留一法”选取训练集和测试集，最后返回准确率为0.8571。(Bias classification is realized by MATLAB, and training set and test set are selected by "leaving one method", and the accuracy of return is 0.8571.)
matlab贝叶斯分类(2)-10折10次交叉验证
- 利用matlab实现贝叶斯分类，采用10折10次交叉验证法选取训练集和测试集，进行循环测试，最后返回准确率为0.9184.另外，文件内含数据源。(The Bias classification is realized by MATLAB, and the training set and test set are selected by 90% off 10 times cross validation method, and the
贝叶斯分类算法
- 5个描述属性，一个分类属性，通过贝叶斯算法实现分类(5 descr iptive attributes, one categorical attribute, is implemented by Bayes algorithm.)
分类器
- 在matlab平台下，简单实现svm分类器功能（数据仓库与数据挖掘课程）(Simple implementation of SVM classifier)
随机森林用于模式分类
- 随机森林用于模式分类识别算法，包含代码和数据(Random Forests for Pattern Classification Recognition Algorithms, Containing Codes and Data)
基于极限学习机ELM的数据分类
- 针对数据分类问题，提出了基于极限学习机的分类方法，将数据样本分为训练样本和测试样本，并采用准确率指标进行评价。(Aiming at the problem of data classification, a classification method based on extreme learning machine is proposed. The data samples are divided into training samp
多条件分类筛选查询代码
- jQuery多条件分类筛选查询代码是一款支持多选条件，更多分类，关键字查询筛选代码。(JQuery multi-condition classification and filtering query code is a kind of code that supports multiple selection conditions, more classification, keyword query and filtering.)
第一次作业_基于分类算法的雷达状态识别
- 第一次作业_基于分类算法的雷达状态识别 对于本数据集中的雷达状态识别，数据降维前使用朴素贝叶斯、支持向量机、神经网络的分类算法对于识别的准确率无太大影响；数据降维后使用神经网络算法最优，支持向量机算法其次，朴素贝叶斯算法较差。此外，训练样本越多，分类准确率有小幅度提高。(First Operation Radar State Recognition Based on Classification Algorithms
SVM分类
- svm 分类算法 需要自己 添加训练序列 全套可以运行(SVM classification)
python猫狗分类程序
- 利用此程序可以对对象进行分类识别，很实用。(This program can be used to classify and recognize objects, which is very practical.)
决策树分类实验（乳腺癌）
- 决策树分类程序，包含使用的数据集和运行结果(Decision tree classifier, including data sets used and running results)
UCI经典二分类数据集
- UCI经典二分类数据集，可借助R或python进行分析学习(UCI Classic Bicategorized Data Set, which can be analyzed and learned by R or Python)
ELM分类
- 内含两个数据集---iris_data和classsim，分别为艾瑞斯花和红酒的分类训练数据。分别用这两个数据集对极限学习机（ELM）进行训练，并测试ELM的分类效果。(It contains two data sets, iris_data and classsim, which are classified training data of Iris Flower and Red Wine respectively. The two
有导师学习神经网络的分类-鸢尾花种类识别
- 有导师学习神经网络的分类-鸢尾花种类识别(Classification of Instructors Learning Neural Networks - Iris Species Identification)
SVM 多分类
- 通过一对多，和多对一的方式，将二分类svm转化成多分类分类器(Through the way of one to many and many to one, the two classification SVM is transformed into a multi classification classifier)